Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 4th International Wo Jianhua Yao,Toma? Vrtovec,Shuo Li Conference procee

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https://doi.org/10.1007/978-3-662-57289-4uous cuts combined with a shape prior. Intensity-based segmentation guarantees high accuracy while the shape prior aims at precision. We tested the algorithm on a set of MR images with visual WM/GM contrast and evaluated it w.r.t. manual GM segmentations. The automated GM segmentations are on a par with the manual results.

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Automated Intervertebral Disc Segmentation Using Deep Convolutional Neural Networks 2015 IVD segmentation challenge datasets, our method achieved a mean Dice overlap coefficient of 89.2% and a mean average absolute surface distance of 1.3?mm. The results achieved by our method are comparable with those achieved by the state-of-the-art methods.

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Conference proceedings 2016Spine Imaging, CSI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. . The 13 workshop papers were carefully reviewed and selected for inclusion in this volume. They aim at reviewing the state-of-the-art techniques, sharing the novel and emerging analysis and visualiza

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Jianhua Yao,Toma? Vrtovec,Shuo LiIncludes supplementary material:

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232690.jpg

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