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

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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. © 2010 Springer-Verlag.

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APA

Changizi, N., Hamarneh, G., Ishaq, O., Ward, A., & Tam, R. (2010). Extraction of the plane of minimal cross-sectional area of the corpus callosum using template-driven segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6363 LNCS, pp. 17–24). https://doi.org/10.1007/978-3-642-15711-0_3

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