Description
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 1st ed. 2017
MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers
Image Processing, Computer Vision, Pattern Recognition, and Graphics Series
Coordinators: Müller Henning, Kelm B. Michael, Arbel Tal, Cai Weidong, Cardoso M. Jorge, Langs Georg, Menze Bjoern, Metaxas Dimitris, Montillo Albert, Wells III William M., Zhang Shaoting, Chung Albert C.S., Jenkinson Mark, Ribbens Annemie
Language: EnglishSubjects for Medical Computer Vision and Bayesian and Graphical...:
Keywords
image analysis; image reconstruction; image segmentation; artificial intelligence; computer vision; medical imaging; learning systems; classification; image enhancement; imaging systems; medical images; image registration; probability; segmentation methods; Support Vector Machines (SVM); classifiers; Bayesian networks; Markov random fields; inverse problems; sensor data fusion
Support: Print on demand
Description
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This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016.
The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions.
The goal of the MCV workshop is to explore the use of "big data? algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images.
The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.