Difference between revisions of "2010 Winter Project Week TBISegmentation"
(Created page with '__NOTOC__ <gallery> Image:PW-SLC2010.png|Projects List </gallery> ==Key Investigators== * Marcel Prastawa, Guido Gerig, University of Uta…') |
|||
| Line 15: | Line 15: | ||
<h3>Objective</h3> | <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. | + | 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. |
</div> | </div> | ||
| Line 22: | Line 22: | ||
<h3>Approach, Plan</h3> | <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. | + | 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. |
</div> | </div> | ||
Revision as of 01:47, 8 December 2009
Home < 2010 Winter Project Week TBISegmentation
Key Investigators
- Marcel Prastawa, Guido Gerig, University of Utah
- Ron Kikinis, BWH
- UCLA
Objective
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.
Approach, Plan
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.
Progress
We have a working program written in C++ using ITK. We will wrap it as a Slicer module.
