2011 Winter Project Week:Extension of ABC to detect pathology categories

Key Investigators

• Utah: Bo Wang, Marcel Prastawa, Guido Gerig

Objective

For traumatic brain injury (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. 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. We will collaborate with UCLA group on this project, they provide the TBI data to us.

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.

References