Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

Author:   Heung-Il Suk ,  Mingxia Liu ,  Pingkun Yan ,  Chunfeng Lian
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   11861
ISBN:  

9783030326913


Pages:   695
Publication Date:   10 October 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings


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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. 

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Author:   Heung-Il Suk ,  Mingxia Liu ,  Pingkun Yan ,  Chunfeng Lian
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2019
Volume:   11861
Weight:   1.080kg
ISBN:  

9783030326913


ISBN 10:   3030326918
Pages:   695
Publication Date:   10 October 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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