Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part I /

Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part I / [electronic resource] : edited by Maxime Descoteaux, Lena Maier-Hein, Alfred Franz, Pierre Jannin, D. Louis Collins, Simon Duchesne. - 1st ed. 2017. - XLVI, 811 p. 343 illus. online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics, 10433 3004-9954 ; . - Image Processing, Computer Vision, Pattern Recognition, and Graphics, 10433 .

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held in Quebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.

9783319661827

10.1007/978-3-319-66182-7 doi


Computer vision.
Artificial intelligence.
Computer science--Mathematics.
Mathematical statistics.
Pattern recognition systems.
Medical informatics.
Computer Vision.
Artificial Intelligence.
Probability and Statistics in Computer Science.
Automated Pattern Recognition.
Health Informatics.

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