My research interests are at the intersection of Machine
Learning, Medical Imaging, and Neuroscience.
So far, I've worked on several projects:
Classification of Alzheimer's disease in MRI and FDG-PET scans, using a
modified LP Boosting framework which is designed to work specifically in
medical images, as well as in a multikernel framework.
I also adapted a Multi-Kernel Learning (MKL) model to explicitly include
outlier detection, and applied it to the same data.
An offshoot of my work with Alzheimer's Disease data
is an investigation into possible outliers in the Alzheimer's Disease
Neuroimaging Initiative (ADNI) dataset. As of this writing, the anomalies
we are picking up could be due either to problems with the Voxel Based
Morphometry (VBM) pre-processing pipeline, or the subjects themselves could
be misdiagnosed. I am currently investigating other approaches to resolve
I've also been
involved in adapting these methods to work with axon bundle tracts which
are segmented from Diffusion Tensor Images (DTI) on the problem of