Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support , 1st ed. 2017 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 Image Processing, Computer Vision, Pattern Recognition, and Graphics Series
Coordonnateurs : Cardoso M. Jorge, Arbel Tal, Carneiro Gustavo, Syeda-Mahmood Tanveer, Tavares João Manuel R.S., Moradi Mehdi, Bradley Andrew, Greenspan Hayit, Papa João Paulo, Madabhushi Anant, Nascimento Jacinto C., Cardoso Jaime S., Belagiannis Vasileios, Lu Zhi
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.
Includes supplementary material: sn.pub/extras
Date de parution : 09-2017
Ouvrage de 385 p.
15.5x23.5 cm
Thèmes de Deep Learning in Medical Image Analysis and Multimodal... :
Mots-clés :
artificial intelligence; classification; classification accuracy; computer architecture; computer vision; computerized tomography; graph theory; image analysis; image processing; image reconstruction; image registration; image segmentation; learning algorithms; learning systems; mammography; medical imaging; neural networks; segmentation methods; Support Vector Machines (SVM)
