Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Müller, Henning (Επιμελητής έκδοσης), Kelm, B. Michael (Επιμελητής έκδοσης), Arbel, Tal (Επιμελητής έκδοσης), Cai, Weidong (Επιμελητής έκδοσης), Cardoso, M. Jorge (Επιμελητής έκδοσης), Langs, Georg (Επιμελητής έκδοσης), Menze, Bjoern (Επιμελητής έκδοσης), Metaxas, Dimitris (Επιμελητής έκδοσης), Montillo, Albert (Επιμελητής έκδοσης), Wells III, William M. (Επιμελητής έκδοσης), Zhang, Shaoting (Επιμελητής έκδοσης), Chung, Albert C.S (Επιμελητής έκδοσης), Jenkinson, Mark (Επιμελητής έκδοσης), Ribbens, Annemie (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Lecture Notes in Computer Science, 10081
• Θέματα: Computer science.; Health informatics.; Mathematical statistics.; Computer science > Mathematics.; Artificial intelligence.; Image processing.; Pattern recognition.; Computer Science.; Image Processing and Computer Vision.; Health Informatics.; Artificial Intelligence (incl. Robotics).; Probability and Statistics in Computer Science.; Math Applications in Computer Science.; Pattern Recognition.
• Φυσική περιγραφή: XIII, 222 p. 75 illus. online resource.
• ISBN: 9783319611884
• ISSN: 0302-9743 ;

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.