Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10081)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
- BAMBI: International Workshop on Bayesian and grAphical Models for Biomedical Imaging
- MCV: International MICCAI Workshop on Medical Computer Vision
Conference proceedings info: BAMBI 2016, MCV 2016.
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (19 papers)
-
MCV Workshop: Brain Imaging
-
MCV Workshop: Lung Imaging
-
MCV Workshop: Segmentation, Detection, and Classification
Other volumes
-
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
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
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
Book Subtitle: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers
Editors: Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, … Annemie Ribbens
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-61188-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-61187-7Published: 04 July 2017
eBook ISBN: 978-3-319-61188-4Published: 30 June 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XIII, 222
Number of Illustrations: 75 b/w illustrations
Topics: Image Processing and Computer Vision, Health Informatics, Artificial Intelligence, Probability and Statistics in Computer Science, Math Applications in Computer Science, Pattern Recognition