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Abstract #2086

Automated Lesion Segmentation in a Marmoset Model of Multiple Sclerosis via Subtraction MRI

Colin Shea 1 , Pascal Sati 1 , Joseph Guy 1 , Emily Leibovitch 1 , Steven Jacobson 1 , Afonso Silva 1 , and Daniel S. Reich 1

1 NINDS, NIH, Bethesda, Maryland, United States

Subtraction MRI is a powerful tool to study new lesions in multiple sclerosis, however unique challenges exist for its application in marmoset models of disease because of the lack of equivalent image processing tools. We developed an automated method to segment new white matter lesions from PD and T2 weighted MRI in marmosets using a new brain tissue atlas, inhomogeneity correction, intensity normalization, subtraction, and object detection. Our method can robustly detect new lesions in serial scans which will enable further study of lesion evolution in marmoset models of multiple sclerosis.

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