A 2.5D \u003cb\u003eColon\u003c/b\u003e Wall Flattening Model for CT-Based Virtual Colonoscopy Huafeng \u003cbr\u003e\nWang1,2, Lihong Li3, Hao Han1, Rui Shi4 ... Based on the flattening results of the \u003cbr\u003e\n\u003cb\u003ecolon\u003c/b\u003e, efforts have been devoted toward its applications for some \u003cb\u003emedical\u003c/b\u003e uses, ...
eBook Title: Machine Learning in Medical Imaging
Author:Guorong Wu,Daoqiang Zhang,Dinggang Shen,Pingkun Yan,Kenji Suzuki,Fei Wang
Published on 2013-09-18 by Springer
This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
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Guorong Wu,Daoqiang Zhang,Dinggang Shen,Pingkun Yan,Kenji Suzuki,Fei Wang
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- Machine Learning in Medical Imaging published by Springer since 2013-09-18 with ISBNs. The book ISBN 13 Code is 9783319022673 and ISBN 10 Code is 3319022679
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