Extraction of the Plane of Minimal Cross-Sectional Area of the Corpus Callosum Using Template-Driven Segmentation
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.
Neda Changizi Ghassan Hamarneh Omer Ishaq Aaron Ward Roger Tam
Medical Image Analysis Lab, Simon Fraser University, Canada Medical Image Analysis Lab, Simon Fraser University, Canada Department of Computer Sciences, Air Uni Medical Image Analysis Lab, Simon Fraser University, Canada Robarts Research Institute, The Universi MS/MRI Research Group, University of British Columbia, Canada
国际会议
北京
英文
17–24
2010-09-01（万方平台首次上网日期，不代表论文的发表时间）