Chris Hinrichs

Research Interests: 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 this issue. 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 classifying Autism.

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