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Abstract #3121

Rapid Semi-Automatic Segmentation of the Spinal Cord from Magnetic Resonance Images

Mark Andrew Horsfield1, Stefania Sala2, Mohit Neema3, Martin Absinta2, Anshika Bakshi3, Maria Pia Sormani4, Mara Rocca2, Rohit Bakshi3, Massimo Filippi2

1Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom; 2Neuroimaging Research Unit, Ospedale San Raffaele, Milan, Italy; 3Laboratory for Neuroimaging Research, Harvard Medical School, Boston, MA, United States; 4Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy

A new semi-automatic method for rapid segmentation of the spinal cord from MR images is presented, based on an active surface (AS) model of the cord surface with intrinsic smoothness constraints. The intra- and inter-observer reproducibilities of cord area measures were evaluated, and compared favorably with an existing cord segmentation method. Correlations between cord area and clinical disability scores confirmed the relevance of the new method in measuring cord atrophy. A novel form of cord visualization is shown, in which the straightened cord center-line forms one coordinate axis of a new image, allowing simple visualization of the cord structure.