Machine Learning in Medical Imaging
10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings
Editors: Suk, H.-I., Liu, M., Yan, P., Lian, C. (Eds.)
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- About this book
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This book constitutes the proceedings of the 10th International Workshop on Machine Learning in Medical Imaging, MLMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.
The 78 papers presented in this volume were carefully reviewed and selected from 158 submissions. They focus on major trends and challenges in the area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
- Table of contents (78 chapters)
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Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization
Pages 1-8
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Spatial Regularized Classification Network for Spinal Dislocation Diagnosis
Pages 9-17
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Globally-Aware Multiple Instance Classifier for Breast Cancer Screening
Pages 18-26
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Advancing Pancreas Segmentation in Multi-protocol MRI Volumes Using Hausdorff-Sine Loss Function
Pages 27-35
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WSI-Net: Branch-Based and Hierarchy-Aware Network for Segmentation and Classification of Breast Histopathological Whole-Slide Images
Pages 36-44
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Table of contents (78 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Machine Learning in Medical Imaging
- Book Subtitle
- 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings
- Editors
-
- Heung-Il Suk
- Mingxia Liu
- Pingkun Yan
- Chunfeng Lian
- Series Title
- Image Processing, Computer Vision, Pattern Recognition, and Graphics
- Series Volume
- 11861
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-32692-0
- DOI
- 10.1007/978-3-030-32692-0
- Softcover ISBN
- 978-3-030-32691-3
- Edition Number
- 1
- Number of Pages
- XVIII, 695
- Number of Illustrations
- 65 b/w illustrations, 245 illustrations in colour
- Topics
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