Fr. 70.00

Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings

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This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017.
The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.

Summary

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017.
The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.

Product details

Assisted by Ta Arbel (Editor), Tal Arbel (Editor), Nematollah K. Batmanghelich (Editor), M. Jorge Cardoso (Editor), Adrian Dalca (Editor), Adrian V. Dalca (Editor), Stanley Durrleman (Editor), Enzo Ferrante (Editor), Enzo Ferrante et al (Editor), Tom Fletcher (Editor), Sarang Joshi (Editor), Mads Nielsen (Editor), Sarah Parisot (Editor), Xavier Pennec (Editor), Mert R. Sabuncu (Editor), Li Shen (Editor), Stefan Sommer (Editor), Aristeidis Sotiras (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 01.01.2017
 
EAN 9783319676746
ISBN 978-3-31-967674-6
No. of pages 250
Dimensions 156 mm x 11 mm x 234 mm
Weight 427 g
Illustrations XV, 250 p. 83 illus.
Series Lecture Notes in Computer Science
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Lecture Notes in Computer Science
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Subjects Natural sciences, medicine, IT, technology > IT, data processing > Application software

C, Künstliche Intelligenz, Data Mining, Artificial Intelligence, Mustererkennung, Wissensbasierte Systeme, Expertensysteme, Computeranwendungen in Industrie und Technologie, computer science, Neural Networks, Computer Vision, Health Informatics, Image Processing and Computer Vision, pattern recognition, Data Mining and Knowledge Discovery, Signal Processing, Automated Pattern Recognition, Health & safety aspects of IT, Optical data processing, Medical imaging, Expert systems / knowledge-based systems, medical images

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