2010 Winter Project Week TBISegmentation - Revision history

Prastawa at 21:17, 8 December 2009

2009-12-08T21:17:21Z

Prastawa at 21:07, 8 December 2009

2009-12-08T21:07:29Z

Prastawa at 20:51, 8 December 2009

2009-12-08T20:51:02Z

Gerig: /* Key Investigators */

2009-12-08T01:56:10Z

Key Investigators

Gerig at 01:50, 8 December 2009

2009-12-08T01:50:32Z

Gerig at 01:47, 8 December 2009

2009-12-08T01:47:55Z

Gerig at 01:47, 8 December 2009

2009-12-08T01:47:22Z

Prastawa: Created page with 'NOTOC Image:PW-SLC2010.png|Projects List ==Key Investigators== * Marcel Prastawa, Guido Gerig, University of Uta…'

2009-12-07T23:59:58Z

Created page with '__NOTOC__ <gallery> Image:PW-SLC2010.png|Projects List </gallery> ==Key Investigators== * Marcel Prastawa, Guido Gerig, University of Uta…'

New page

__NOTOC__
<gallery>
Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]

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==Key Investigators==
* Marcel Prastawa, Guido Gerig, University of Utah
* Ron Kikinis, BWH
* UCLA

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<h3>Objective</h3>
Traumatic Brain Injury (TBI) is caused by severe impact to the brain, which may result in skull fracture, lesions, and internal bleeding. Treatment for TBI involves significant surgery. The complication involved necessitates multiple imaging scans, such as CT for planning the surgeries and multimodal MRI for assessing the surgical treatment. We plan to study the process that occur in typical TBI patients and determine regions that are damaged and how they behave. The first step in analyzing these patient data is the segmentation of the different regions (edema, bleeding, etc) from multiple MRI modalities (T1w, T2w, T2w-blood, SWI).

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<h3>Approach, Plan</h3>
We propose an atlas based segmentation method, which makes use of normative data (spatial and intensity) for isolating abnormal regions that are likely due to injury.

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<h3>Progress</h3>
We have a working program written in C++ using ITK. We will wrap it as a Slicer module.

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==References==

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 <gallery>
 Image:PW-SLC2010.png|[[2010_Winter_Project_Week#Projects|Projects List]]
-Image:TBI_modalities.png|TBI modalities
+Image:TBI_modalities.png | TBI modalities
-Image:TBI_lesion_shunt.png|Segmentation result with lesion and shunt
+Image:TBI_lesion_shunt.png | Segmentation result with lesion and shunt
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 <h3>Approach, Plan</h3>
-Preferably, such a procedure should be automatic given the presence of small-scale pathology such as lesions, bleedings and ventricular shape alterations, or involve efficient, easy and intuitive expert interaction to support an automated classification algorithm. We propose an atlas based multi-modal segmentation method (ABC: Atlas-Based Classification), which makes use of normative data (spatial and intensity) for isolating abnormal regions that are likely due to injury.
+Preferably, such a procedure should be automatic given the presence of small-scale pathology such as lesions, bleedings and ventricular shape alterations, or involve efficient, easy and intuitive expert interaction to support an automated classification algorithm. We propose an atlas based multi-modal segmentation method (''ABC: Atlas-Based Classification''), which makes use of normative data (spatial and intensity) for isolating abnormal regions that are likely due to injury.
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 <h3>Progress</h3>
-We have a working ptototype program of ABC written in C++ using ITK. We will wrap it as a Slicer module and will systematically test its performance on various TBI datasets.
+We have a working ptototype program of ''ABC'' written in C++ using ITK. ''ABC'' incorporates image co-registration, atlas template registration, bias field correction, and tissue classification into an efficient workflow. We will wrap it as a Slicer module and will systematically test its performance on various TBI datasets. These tests will include co-registration of DTI and structural MRI for joint analysis of white matter tracts, brain anatomy and lesions.
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 <h3>Objective</h3>
-Traumatic Brain Injury (TBI) is caused by severe impact to the brain, which may result in skull fracture, lesions, and internal bleeding. Full assessment of these injuries is possible via multi-modality imaging, here T1w, T2, T1-postcontrast, Flair (fluid attenuated inversion recovery), SWI (susceptibility weighted imaging), DTI). Joint analysis of these modalities requires co-registration of these sets which come with different orientations, spatial resolution and head coverage. Segmentation of brain tissue, fluid and pathology requires efficient procedures for multi-modal analysis of images with classification of lesions. Preferably, such a procedure should be automatic given the presence of small-scale pathology such as lesions, bleedings and ventricular shape alterations, or involve efficient, easy and intuitive expert interaction to support an automated classification algorithm.
+Traumatic Brain Injury (TBI) is caused by severe impact to the brain, which may result in skull fracture, lesions, and internal bleeding. Full assessment of these injuries is possible via multi-modality imaging, here T1w, T2, T1-postcontrast, Flair (fluid attenuated inversion recovery), SWI (susceptibility weighted imaging), DTI). Joint analysis of these modalities requires co-registration of these sets which come with different orientations, spatial resolution and head coverage. Segmentation of brain tissue, fluid and pathology requires efficient procedures for multi-modal analysis of images with classification of lesions.
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← Older revision	Revision as of 21:17, 8 December 2009
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2010 Winter Project Week TBISegmentation - Revision history

Prastawa at 21:17, 8 December 2009

Prastawa at 21:07, 8 December 2009

Prastawa at 20:51, 8 December 2009

Gerig: /* Key Investigators */

Gerig at 01:50, 8 December 2009

Gerig at 01:47, 8 December 2009

Gerig at 01:47, 8 December 2009

Prastawa: Created page with '__NOTOC__ Image:PW-SLC2010.png|Projects List ==Key Investigators== * Marcel Prastawa, Guido Gerig, University of Uta…'

Prastawa: Created page with 'NOTOC Image:PW-SLC2010.png|Projects List ==Key Investigators== * Marcel Prastawa, Guido Gerig, University of Uta…'