24 March 2016 Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations
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Abstract
In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.
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Han Sang Lee, Han Sang Lee, Hyeun A. Kim, Hyeun A. Kim, Hyeonjin Kim, Hyeonjin Kim, Helen Hong, Helen Hong, Young Cheol Yoon, Young Cheol Yoon, Junmo Kim, Junmo Kim, "Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97853H (24 March 2016); doi: 10.1117/12.2216630; https://doi.org/10.1117/12.2216630
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