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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