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Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefull...

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Bibliographic Details
Other Authors: Ourselin, Sebastien (Editor), Joskowicz, Leo (Editor), Sabuncu, Mert R. (Editor), Unal, Gozde (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2016, 2016
Edition:1st ed. 2016
Series:Image Processing, Computer Vision, Pattern Recognition, and Graphics
Subjects:
Computer Graphics
Health Informatics
Computer Vision
Medical Informatics
Artificial Intelligence
Radiology
Automated Pattern Recognition
Pattern Recognition Systems
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016  |h Elektronische Ressource  |b 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II  |c edited by Sebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells 
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520 |a The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis, brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR imageanalysis 

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