Difference between revisions of "2011 Winter Project Week:Extension of ABC to detect pathology categories"
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| + | Image:PW-SLC2011.png|[[2011_Winter_Project_Week#Projects|Projects List]] | ||
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==Key Investigators== | ==Key Investigators== | ||
* Utah: Bo Wang, Marcel Prastawa, Guido Gerig | * Utah: Bo Wang, Marcel Prastawa, Guido Gerig | ||
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<h3>Objective</h3> | <h3>Objective</h3> | ||
| − | + | Traumatic brain injury (TBI) occurs when an external force traumatically injures the brain. TBI is a major cause of death and disability worldwide, especially in children and young adults. TBI affects 1.4 million Americans annually. | |
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| + | On anatomical MRI scans, for quantitatively analyze the cortical thickness, white matter changes, we need to have a good segmentation on TBI images. However, for TBI data, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury. | ||
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| + | UCLA group has been working on this research topic for years. We will collaborate with UCLA group on this project. We will develop end-to-end processing approaches using the NA-MIC Kit to investigate alterations in cortical thickness, subsequent ventricular, and white matter changes in patients with TBI and in age-matched controls. | ||
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Revision as of 22:33, 16 December 2010
Home < 2011 Winter Project Week:Extension of ABC to detect pathology categories
Key Investigators
- Utah: Bo Wang, Marcel Prastawa, Guido Gerig
- UCLA: Jack Van Horn
Objective
Traumatic brain injury (TBI) occurs when an external force traumatically injures the brain. TBI is a major cause of death and disability worldwide, especially in children and young adults. TBI affects 1.4 million Americans annually.
On anatomical MRI scans, for quantitatively analyze the cortical thickness, white matter changes, we need to have a good segmentation on TBI images. However, for TBI data, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.
UCLA group has been working on this research topic for years. We will collaborate with UCLA group on this project. We will develop end-to-end processing approaches using the NA-MIC Kit to investigate alterations in cortical thickness, subsequent ventricular, and white matter changes in patients with TBI and in age-matched controls.
Approach, Plan
ABC (Atlas-Based Classification) is a fully automatic segmentation method in our group. It can process arbitrary number of channels/modalities by co-registration, it integrates brain stripping, bias correction and segmentation into one optimization framework. Atlas template is used as spatial priors for tissue categories, atlas-subject warping can be deformable. We want to extend ABC to detect pathology categories, with tests on TBI images. In the first step, we want to add user interaction to the ABC framework.
Progress
Currently, we have applied ABC to process TBI data to get the segmentation of white matter, gray matter and cerebrospinal fluid. We also added user-supervised level-set segmentation to detect the lesions. The current results are promising.
