Registration using Embedded Maps
Structural brain changes that occur during the process of normal aging are of great interest to neuroscientists investigating age-related changes in cognitive function. A variety of techniques currently exist to identify group differences in brain anatomy with the greatest focus having been placed on cortical anatomy. Although cortical anatomy is of considerable significance, the underlying white matter tracts are at great risk in the aged brain. Patchy white matter lesions referred to as leukoaraiosis (LA) have long been identified radiologically as T2-weighted hyperintensities in older adults.
Techniques such as voxel-based morphometry (VBM), deformation-based morphometry (DBM), or tissue thickness measurements allow for quantitative comparisons of white matter in a regionally specific manner. However, VBM is dependent upon segmentation algorithms to measure tissue density, a task difficult in images displaying the diffuse contrast changes associated with LA. Similarly, DBM is dependent on registration algorithms to establish a spatial correspondence between images. Unfortunately, current image registration methods do not perform effectively in regions where tissue contrast has changed, such as in leukoaraiosis.
The goal of this project is to evaluate the relationship between changes in cognitive function and cerebral white matter in older adults. Since current VBM and DBM methods cannot be applied to subjects with leukoaraiosis, the project will expand current image registration techniques to accommodate topological changes in the images.
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- XNAT Project Identifying Age Related Atrophy Using Levelset Registration of Embedded Maps
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