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Machine Learning in Medical Imaging

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10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

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Beschreibung

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. 

Autor*in

Heung-Il Suk

Themen in »Machine Learning in Medical Imaging«

artificial intelligence automatic segmentations ct image image analysis image reconstruction image registration image segmentation learning algorithms medical images neural networks recurrent neural networks segmentation methods Support Vector Machines (SVM)

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Details

ISBN: 9783030326913
Verlag: Springer International Publishing
Erscheinung: 10.10.2019

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