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Tal Arbel, Andrew Bradley, M. Jorge Cardoso, Gustavo Carneiro, Hayit Greenspan, Tanveer Syeda- Mahmood, Mehdi Moradi, JoĆo Paulo Papa, Tanveer Syeda-Mahmood, JoĆo Manuel R.S. Tavares (Beteiligte)

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support


Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, Proceedings
Herausgegeben von Cardoso, M. Jorge; Arbel, Tal; Carneiro, Gustavo; Syeda-Mahmood, Tanveer; Tavares, JoĆo Manuel R.S.; Moradi, Mehdi
1st ed. 2017. 2017. xix, 385 S. 169 SW-Abb. 235 mm
Verlag/Jahr: SPRINGER, BERLIN; SPRINGER INTERNATIONAL PUBLISHING 2017
ISBN: 3-319-67557-5 (3319675575)
Neue ISBN: 978-3-319-67557-2 (9783319675572)

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This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017.

The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.