Generalized Tensor-Based Morphometry for the Analysis of Brain MRI and Diffusion Tensor Images

Speaker: Natasha Lepore,
Department of Neurology, UCLA School of MedicineAbstract:
Tensor-based morphometry (TBM) is widely used in computational anatomy as a means to under-stand shape variation between structural brain images. A 3D nonlinear registration technique is used to align all brain images to a common neuroanatomical template, and the deformation fields are analyzed statistically to identify group differences in anatomy in TBM, differences between images are usually computed solely from the determinants of the Jacobian matrices J that are associated with the deformation fields computed by the registration procedure. The determinants give the local volume increases and reductions of the image from the registration. However, only the magnitude of the expansions or contractions is examined, while the directional components of the changes are ignored. We remedy this problem by computing both shape and volume change statistics using the deformation tensors, defined as (JT J)1/2.Furthermore, detection power depends on several factors, and key among these is the quality of the non-linear registration, which depends both on the registration algorithm and on the common target to which all images are mapped. We designed a new fluid registration code which penalizes deviations from zero deformation tensors. To reduce dependence on the choice of individual template, we average deformation tensors from multiple registrations to individual reference images. The method will be demonstrated on to two data sets. The first consists of MR images from 26 HIV/AIDS patients and 14 matched healthy controls. The registration and statistics can both be extended in a straightforward way to the analysis of diffusion tensor images. Our second set s composed of both MR and DT images from 23 pairs of monozygotic and 23 pairs of dizygotic twins. For the HIV/AIDS patients, widespread atrophy was found throughout the brain, with greater effect sizes in the corpus callosum and the basal ganglia. In MZ twins, for both MR and DT images, high intra-pair correlation was found for all deep white matter regions, including the corpus callosum. This correlation was weaker in DZ twins, as expected for genetically determined traits.Bio:
I graduated with a Bsc in physics and mathematics at the University of Montreal. I then obtained a masters in Applied Mathematics at Cambridge University in England. My PhD work was carried out at Harvard University, and dealt with the theory of quantum chaos. For the last 3.5 years, I have been a postdoctoral fellow at the laboratory of Neuro Imaging, in Dr Toga's lab, but working particularly with Dr Paul Thompson. We worked on several projects involving brain MRI and DTI data, including improvements to Tensor-Based Morphometry, surface and volume registration, ventricle segmentation, and their application to various datasets including healthy twins, blind subjects, deaf subjects, HIV/AIDS patients, autism and Alzheimer's disease.Hosted by: Professor Richard Leahy

Location: Seaver Science Library (SSL) - 150

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