https://www.na-mic.org/w/api.php?action=feedcontributions&feedformat=atom&user=Sbr 2026-05-15T12:59:19Z User contributions MediaWiki 1.33.0 https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22961 2008-03-16T23:59:08Z

<p>Sbr: /* Recommended reading before the class */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> The following papers describe a number of IMRI applications currently under development at the Surgical Planning Laboratory. Please read the paper on neurosurgery and be familiar with the other applications.<br /> <br /> '''Image-guided Neurosurgery at Brigham and Women’s Hospital''' <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> '''MR-guided prostate interventions'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> '''Current status and future potential of MRI-guided focused ultrasound surgery'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> '''MRI-guided cryotherapy'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical imaging for guiding and navigating surgery?<br /> #What are the technologies involved in image guided therapy? List and briefly describe them in the order of workflow.<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided intra-operative image guided therapy?<br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> #What are the main clinical applications in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summarize them.<br /> #What do you think is an unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22960 2008-03-16T23:57:36Z

<p>Sbr: /* Recommended reading before the class */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> '''MR-guided prostate interventions'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> '''Image-guided Neurosurgery at Brigham and Women’s Hospital''' <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> '''Current status and future potential of MRI-guided focused ultrasound surgery'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> '''MRI-guided cryotherapy'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical imaging for guiding and navigating surgery?<br /> #What are the technologies involved in image guided therapy? List and briefly describe them in the order of workflow.<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided intra-operative image guided therapy?<br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> #What are the main clinical applications in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summarize them.<br /> #What do you think is an unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22959 2008-03-16T23:57:19Z

<p>Sbr: /* Recommended reading before the class */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> '''MR-guided prostate interventions'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> '''Image-guided Neurosurgery at Brigham and Women’s Hospital''' <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> '''Current status and future potential of MRI-guided focused ultrasound surgery'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> '''<br /> MRI-guided cryotherapy'''<br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical imaging for guiding and navigating surgery?<br /> #What are the technologies involved in image guided therapy? List and briefly describe them in the order of workflow.<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided intra-operative image guided therapy?<br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> #What are the main clinical applications in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summarize them.<br /> #What do you think is an unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22956 2008-03-16T23:50:01Z

<p>Sbr: /* Homework problems */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical imaging for guiding and navigating surgery?<br /> #What are the technologies involved in image guided therapy? List and briefly describe them in the order of workflow.<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided intra-operative image guided therapy?<br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> #What are the main clinical applications in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summarize them.<br /> #What do you think is an unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22955 2008-03-16T23:49:40Z

<p>Sbr: /* Homework problems */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical imaging for guiding and navigating surgery?<br /> #What are the technologies involved in image guided therapy? List and briefly describe them in the order of workflow.<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical applications in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summarize them.<br /> #What do you think is an unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22954 2008-03-16T23:47:30Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR imaging (IMRI) for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications include liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorporation of these images can provide information that can not be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Recommended exercise before the class===<br /> <br /> If you are interested in learning how we process pre-operative images in preparation for MRI-guided therapy, download the free software slicer following the instructions in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the courses available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22939 2008-03-14T21:28:50Z

<p>Sbr: /* Introdcution */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> If you are interested in learing how we process pre-operative images in preparation for MRI-guided therapy, dowload free software slicer following the instruction in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the course available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introduction===<br /> We will present the overview of the MRI-guided therapy and technologies involved in it.<br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22938 2008-03-14T21:28:08Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner.<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> If you are interested in learing how we process pre-operative images in preparation for MRI-guided therapy, dowload free software slicer following the instruction in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the course available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introdcution===<br /> <br /> <br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22937 2008-03-14T21:27:34Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this laboratory course, we will present our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> If you are interested in learing how we process pre-operative images in preparation for MRI-guided therapy, dowload free software slicer following the instruction in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the course available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introdcution===<br /> <br /> <br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22936 2008-03-14T21:27:06Z

<p>Sbr: /* Reccommended exersie before the class */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> If you are interested in learing how we process pre-operative images in preparation for MRI-guided therapy, dowload free software slicer following the instruction in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Among the course available in the web page, we suggest you take the following topics..<br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introdcution===<br /> <br /> <br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22935 2008-03-14T21:26:18Z

<p>Sbr: /* Reccommended exersie before the class */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> If you are interested in learing how we process pre-operative images in preparation for MRI-guided therapy, dowload free software slicer following the instruction in the &quot;Slicer 101&quot; page below. <br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> The Slicer 101 tutorial will let you learn <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introdcution===<br /> <br /> <br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22934 2008-03-14T21:24:19Z

<p>Sbr: </p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ===Reccommended exersie before the class===<br /> <br /> <br /> <br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> <br /> <br /> <br /> ==On the day of the lab....==<br /> <br /> ===Introdcution===<br /> <br /> <br /> <br /> ===Live demonstration===<br /> <br /> <br /> ==Homework problems==<br /> <br /> #What is the benefit of medical images for guiding and navigating surgery?<br /> #What are the technology involved in Image guided Therapy? List and briefly describe them in the order of workflow?<br /> #What is the patient-to-image registration? What kind of mathematical process is involved in the patient-to-image registration?<br /> #What is Target Registration Error, Fiducial Registration Error, and Fiducial Localization error?<br /> #What is the difference between pre-operative image guided therapy and intra-operative image guided therapy?<br /> #What is the benefit of MRI-guided Intra-operative image guided therapy?<br /> <br /> #How would you solve the problem that intra-operative MRI has inherently less quality than pre-operative images?<br /> <br /> #What are the main clinical application in MRI-guided therapy?<br /> #From PubMed, find three interesting paper on MRI-guided therapy and summerize them.<br /> #What do you think is unchallenged clinical target in MRI-guided therapy?</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22933 2008-03-14T21:16:34Z

<p>Sbr: /* Lab write-up expectations */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: <br /> <br /> <br /> #We will review the background of MRI-guided therapy and Image guided therapy in general.<br /> the following slide will be presented.<br /> <br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> <br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22932 2008-03-14T21:15:39Z

<p>Sbr: </p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> <br /> ==Background:==<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> <br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading before the class===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: <br /> <br /> <br /> #We will review the background of MRI-guided therapy and Image guided therapy in general.<br /> the following slide will be presented.<br /> <br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22931 2008-03-14T21:14:06Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> ==Background:==<br /> In comparison to other medical imaging modalities, magnetic resonance imaging (MRI) has clear advantages in its volumetric scanning capabilities, tissue discrimination and the detailed delineation of anatomic features. Additionally, MR imaging has unique potential capabilities for functional physiologic imaging and temperature mapping. These features of MR imaging motivated the development of intraoperative MR (IMRI) imaging for guidance of biopsy, thermal ablation and other surgical procedures. The major application of IMRI has been neurosurgical cases, including biopsy, drainage and tumor ablation. Other applications were liver biopsy and sinus endoscopic surgery. <br /> <br /> There are many benefits in using pre-operatively obtained MRI as part of an analysis of imagery from IMRI. For example, IMRI has some limitations in its imaging capability in comparison to pre-operative MRI from conventional diagnostic MR scanner, since requirements for interventional use (for example, the use of surface coils for good access) have some impact on the imaging capability. After performing a registration that determines the proper spatial relationship between the pre-operative MRI and IMRI, one could compare and determine whether changes in tissue structure have occurred. For instance, this would be extremely useful in evaluating the extent of tumor. <br /> <br /> We can further appreciate the benefit of pre-operative image, if we can co-register imagery from other modalities than MRI. Currently, we can register computed tomography (CT), T1- and T2-weighted MRI: magnetic resonance angiography (MRA), single photon emission computed tomography (SPECT). Incorpolatin of these images can provide information that can bot be deduced from regular MRI.<br /> In general, utilizing pre- and intra-operative image registration would allow a surgeon to more precisely identify and avoid critical structures and more accurately locate pathological tissues during a procedure.<br /> <br /> In this paper, we will report our approach to register pre-operative image to intra-operative MRI and use co-registered images to navigate neurosurgeries. We will first outline the registration method through maximization of mutual information. Then, the comprehensive accuracy study of the registration and clinical application of the method are introduced. In the clinical application section, we will introduce our engineering and computational setup to achieve online and near real-time registration and navigation in an inerventional MRI scanner (Signa SP, General Electric Medical Systems, Milwaukee, WI).<br /> An example scenario<br /> <br /> ===Recommended reading===<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22930 2008-03-14T20:55:33Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> ==Background:==<br /> <br /> The background should provide brief descriptions of the specific imaging technology and image processing techniques (i.e. a few paragraphs) and should reference seminal papers for more detail.<br /> Reading References<br /> <br /> You should include a list of papers on the specific techniques used in the lab, as well as a few more general background references on the technology (e.g. MR basics) for those that might not have taken HST 561. I will check with Alan Jasanoff (instructor for HST 561) to see if we can post some of his background material. Total reading material can be significant; please send me pdf copies and I will post them in the course locker.<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1247<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22929 2008-03-14T20:55:10Z

<p>Sbr: /* Background: */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> ==Background:==<br /> <br /> The background should provide brief descriptions of the specific imaging technology and image processing techniques (i.e. a few paragraphs) and should reference seminal papers for more detail.<br /> Reading References<br /> <br /> You should include a list of papers on the specific techniques used in the lab, as well as a few more general background references on the technology (e.g. MR basics) for those that might not have taken HST 561. I will check with Alan Jasanoff (instructor for HST 561) to see if we can post some of his background material. Total reading material can be significant; please send me pdf copies and I will post them in the course locker.<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1225<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=1244<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22928 2008-03-14T20:53:44Z

<p>Sbr: /* Introduction */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:robot.png|200px]]<br /> [[Image:slicer.png|200px]]<br /> <br /> ==Background:==<br /> <br /> The background should provide brief descriptions of the specific imaging technology and image processing techniques (i.e. a few paragraphs) and should reference seminal papers for more detail.<br /> Reading References<br /> <br /> You should include a list of papers on the specific techniques used in the lab, as well as a few more general background references on the technology (e.g. MR basics) for those that might not have taken HST 561. I will check with Alan Jasanoff (instructor for HST 561) to see if we can post some of his background material. Total reading material can be significant; please send me pdf copies and I will post them in the course locker.<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=File:Slicer.png&diff=22927 2008-03-14T20:48:57Z

<p>Sbr: </p> <hr /> <div></div>

Sbr https://www.na-mic.org/w/index.php?title=File:Robot.png&diff=22926 2008-03-14T20:48:33Z

<p>Sbr: </p> <hr /> <div></div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22925 2008-03-14T20:47:57Z

<p>Sbr: /* Introduction */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:robot.png|[[Image:robot.png|Image:robot.png]]]]<br /> [[Image:slicer.png|[[Image:slicer.png|Image:slicer.png]]]]<br /> <br /> ==Background:==<br /> <br /> The background should provide brief descriptions of the specific imaging technology and image processing techniques (i.e. a few paragraphs) and should reference seminal papers for more detail.<br /> Reading References<br /> <br /> You should include a list of papers on the specific techniques used in the lab, as well as a few more general background references on the technology (e.g. MR basics) for those that might not have taken HST 561. I will check with Alan Jasanoff (instructor for HST 561) to see if we can post some of his background material. Total reading material can be significant; please send me pdf copies and I will post them in the course locker.<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

Sbr https://www.na-mic.org/w/index.php?title=Events:HST-563-March2008&diff=22924 2008-03-14T20:47:28Z

<p>Sbr: /* Introduction */</p> <hr /> <div>=Lab date/time/location=<br /> *March 19, 2008<br /> *[Direction http://www.spl.harvard.edu/pages/Directions]<br /> <br /> <br /> =Introduction=<br /> <br /> [[Image:Dhhs_logo.png|[[Image:Dhhs_logo.png|Image:Dhhs_logo.png]]]]<br /> <br /> <br /> ==Background:==<br /> <br /> The background should provide brief descriptions of the specific imaging technology and image processing techniques (i.e. a few paragraphs) and should reference seminal papers for more detail.<br /> Reading References<br /> <br /> You should include a list of papers on the specific techniques used in the lab, as well as a few more general background references on the technology (e.g. MR basics) for those that might not have taken HST 561. I will check with Alan Jasanoff (instructor for HST 561) to see if we can post some of his background material. Total reading material can be significant; please send me pdf copies and I will post them in the course locker.<br /> <br /> <br /> http://www.spl.harvard.edu/pages/Special:PubDB_View?dspaceid=294<br /> <br /> ==Overview/goals of lab exercise==<br /> <br /> <br /> #Background reading: 1-2 review style papers that cover the basics/fundamentals of the techniques at a general level. This should be enough to understand the lab demonstration. You can just send these to me and I'll post them on the website.<br /> <br /> #Lab demonstration: the 2 hr on-site session at the Surgical Planning Laboratory and Brigham and Women's Hospital.<br /> <br /> '''Computer assisted''' <br /> <br /> #A small number of questions to answer about the lab demonstration and background reading to test comprehension.<br /> <br /> ==Lab write-up expectations==<br /> a five page report with answers to the pre-lab homework and lab exercises.<br /> <br /> =Pre-lab Exercises=<br /> <br /> <br /> ==Tutorial==<br /> <br /> We will take series of tutorials available at<br /> http://wiki.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101<br /> <br /> <br /> <br /> Topics we cover will be<br /> <br /> <br /> <br /> *Data Loading and Visualization<br /> *Data Saving<br /> *Manual Segmentation<br /> *Level-Set Segmentation<br /> *Automatic Brain Segmentation<br /> *Registration<br /> *Diffusion Tensor Imaging Analysis<br /> *Nrrd File Format<br /> *Dicom to Nrrd Conversion<br /> *Functional Magnetic Resonace Imaging Analysis<br /> <br /> ==Homework problems==<br /> <br /> Please read either one of the following literature before the class.<br /> <br /> =Lab Exercises=<br /> <br /> The lab exercise should be thought of as the take-home portion of the lab which forms the bulk of the lab-writeup (the finished document that gets graded). It should include some sort of data processing, perhaps including a walk-through/example of the image processing technique, code writing (preferable in matlab or other widely-known software package), and questions to probe understanding of the material. I’m sure this section will vary the most from lab to lab, but it should at least include a series of questions that can be answered (and graded!).<br /> ==Description of data/process==<br /> <br /> This section should link the student to the data (e.g. found in course locker) and have simple instructions about what to do with the data (e.g. FFT the data series). Questions can be interspersed.<br /> ==Questions==<br /> <br /> Questions can be actual problems (e.g. remove the shot noise from image A) or more open-ended discussion questions (e.g. what are the advantages/disadvantages of signal averaging?)</div>

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