Enhanced Software Tools for Detecting Anatomical Differences in Image Data Sets

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Project Summary Morphometric analysis is a primary algorithmic tool to discover disease and drug related effects on brain anatomy. Neurological degeneration and disease manifest in subtle and varied changes in brain anatomy that can be non-local in nature and affect amounts of white and gray matter as well as relative positioning and shapes of local brain anatomy. State-of-the-art morphometry methods focus on local matter distribution or on shape variations of apriori selected anatomies but have difficulty in detecting global or regional deterioration of matter; an important effect in many neurodegenerative processes. The proposal team recently developed a morphometric analysis based on unbalanced optimal transport, called UTM, that promises to be capable of discovering local and global alteration of matter without the need to apriori select an anatomical region of interest. The goal of this proposal is to develop the UTM technology into a software tool for automated high-throughput screening of large neurological image data sets. A more sensitive automated morphometric analysis tool will help researchers to discover neurological effects related to disease and lead to more efficient screening for drug related effects.