Extraction of the plane of minimal cross-sectional area of the corpus callosum using template-driven segmentation

Authors:
Neda Changizi;Ghassan Hamarneh;Omer Ishaq;Aaron Ward;Roger Tam
Affiliations:
Medical Image Analysis Lab, Simon Fraser University, Canada;Medical Image Analysis Lab, Simon Fraser University, Canada;Medical Image Analysis Lab, Simon Fraser University, Canada and Department of Computer Sciences, Air University, Pakistan;Medical Image Analysis Lab, Simon Fraser University, Canada and Robarts Research Institute, The University of Western Ontario, Canada;MSRI Research Group, University of British Columbia, Canada
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Year:
2010

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Abstract

Changes in corpus callosum (CC) size are typically quantified in clinical studies by measuring the CC cross-sectional area on a midsagittal plane. We propose an alternative measurement plane based on the role of the CC as a bottleneck structure in determining the rate of interhemispheric neural transmission. We designate this plane as the Minimum Corpus Callosum Area Plane (MCCAP), which captures the cross section of the CC that best represents an upper bound on interhemispheric transmission. Our MCCAP extraction method uses a nested optimization framework, segmenting the CC as it appears on each candidate plane, using registration-based segmentation. We demonstrate the robust convergence and high accuracy of our method for magnetic resonance images and present preliminary clinical results showing higher sensitivity to disease-induced atrophy.