Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11044)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Conference series link(s): GRAIL: International Workshop on Graphs in Biomedical Image Analysis, Beyond MIC: International Workshop on Integrating Medical Imaging and Non-Imaging Modalities for Healthcare Challenges
Conference proceedings info: GRAIL 2018, Beyond MIC 2018.
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (10 papers)
-
Front Matter
-
Proceedings of the Second Workshop on GRaphs in biomedicAl Image anaLysis
-
Front Matter
-
-
Proceedings of the First Workshop Beyond MIC: Integrating Imaging and Non-imaging Modalities for Healthcare Challenges
-
Front Matter
-
-
Back Matter
Other Volumes
-
Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities
About this book
This book constitutes the refereed joint proceedings of the Second International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2018 and the First International Workshop on Integrating Medical Imaging and Non-Imaging Modalities, Beyond MIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.
The 6 full papers presented at GRAIL 2018 and the 5 full papers presented at BeYond MIC 2018 were carefully reviewed and selected. The GRAIL papers cover a wide range of develop graph-based models for the analysis of biomedical images and encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. The Beyond MIC papers cover topics of novel methods with significant imaging and non-imaging components, addressing practical applications and new datasets
Keywords
- artificial intelligence
- Bayesian networks
- classification
- cluster analysis
- computer vision
- data mining
- face recognition
- feature selection
- graph theory
- image analysis
- image processing
- image reconstruction
- learning systems
- medical imaging
- neural networks
- pattern recognition
- signal processing
- Support Vector Machines (SVM)
- algorithm analysis and problem complexity
Editors and Affiliations
-
University College London, London, UK
Danail Stoyanov
-
University of Leeds, Leeds, UK
Zeike Taylor
-
CONICET/Universidad Nacional del Litoral, Santa Fe, Argentina
Enzo Ferrante
-
Harvard Medical School, Cambridge, USA
Adrian V. Dalca
-
Sunnybrook Health Science Centre, Toronto, Canada
Anne Martel
-
Deutsches Krebsforschungszentrum, Heidelberg, Germany
Lena Maier-Hein
-
AimBrain, London, UK
Sarah Parisot
-
University of Pennsylvania, Philadelphia, USA
Aristeidis Sotiras, Li Shen
-
University of Oxford, Oxford, UK
Bartlomiej Papiez
-
Cornell University, Ithaca, USA
Mert R. Sabuncu
Bibliographic Information
Book Title: Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities
Book Subtitle: Second International Workshop, GRAIL 2018 and First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings
Editors: Danail Stoyanov, Zeike Taylor, Enzo Ferrante, Adrian V. Dalca, Anne Martel, Lena Maier-Hein, Sarah Parisot, Aristeidis Sotiras, Bartlomiej Papiez, Mert R. Sabuncu, … Li Shen
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-00689-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-030-00688-4Published: 16 September 2018
eBook ISBN: 978-3-030-00689-1Published: 15 September 2018
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVI, 101
Number of Illustrations: 26 b/w illustrations
Topics: Image Processing and Computer Vision, Mathematics of Computing, Artificial Intelligence, Algorithm Analysis and Problem Complexity, Data Structures and Information Theory