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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, Quebec City, QC, Canada, September 14, Proceedings

by (author) M. Jorge Cardoso

edited by Tal Arbel, Gustavo Carneiro, Tanveer Syeda-Mahmood, João Manuel R.S. Tavares, Mehdi Moradi, Andrew Bradley & Hayit Greenspan

Publisher
Springer Nature
Initial publish date
Sep 2017
Category
Games, Intelligence (AI) & Semantics, Hospital Administration & Care
  • Paperback / softback

    ISBN
    9783319675572
    Publish Date
    Sep 2017
    List Price
    $102.5

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Description

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.

 

 

About the authors

M. Jorge Cardoso's profile page

Tal Arbel's profile page

Gustavo Carneiro's profile page

Tanveer Syeda-Mahmood's profile page

João Manuel R.S. Tavares' profile page

Mehdi Moradi's profile page

Andrew Bradley was born in Melbourne, Australia, in 1962. An avid outdoorsman and world traveller, Andrew has spent time in Toronto, Los Angeles and New York. He has lived and worked in his adopted province, Alberta, since 1996. A self-taught photographer, Andrew is also a pilot with an eye for aerial views.

Andrew Bradley's profile page

Hayit Greenspan's profile page

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