Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

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

M. Jorge Cardoso and Others
    • $39.99
    • $39.99

Publisher Description

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.

GENRE
Computers & Internet
RELEASED
2017
September 6
LANGUAGE
EN
English
LENGTH
265
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
7.4
MB

More Books by M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang Joshi, Nematollah K. Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman & Stefan Sommer

Domain Adaptation and Representation Transfer Domain Adaptation and Representation Transfer
Domain Adaptation and Representation Transfer
2023
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health
2022
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
2021
Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health
Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health
2021
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning
2020
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data
2019