Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

  • Dajiang Zhu
  • Jingwen Yan
  • Heng Huang
  • Li Shen
  • Paul M. Thompson
  • Carl-Fredrik Westin
  • Xavier Pennec
  • Sarang Joshi
  • Mads Nielsen
  • Tom Fletcher
  • Stanley Durrleman
  • Stefan Sommer
Publisher:Springer NatureISBN 13: 9783030332266ISBN 10: 3030332268

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Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy is written by Dajiang Zhu and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3030332268 (ISBN 10) and 9783030332266 (ISBN 13).

This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.