Noemi Gyori (editor) - Computational Diffusion MRI: International MICCAI Workshop, Lima, Peru, October 2020 (Mathematics and Visualization)

The series Mathematics and Visualization is intended to further the fruitful relationship between mathematics and visualization. It covers applications of visualization techniques in mathematics, as well as mathematical theory and methods that are used for visualization. In particular, it emphasizes visualization in geometry, topology, and dynamical systems; geometric algorithms; visualization algorithms; visualization environments; computer aided geometric design; computational geometry; image processing; information visualization; and scientific visualization. Three types of books will appear in the series: research monographs, graduate textbooks, and conference proceedings.

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It is our great pleasure to present the proceedings of the 2020 International Workshop on Computational Diffusion MRI (CDMRI20). CDMRI20 was held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which took place virtually on October 8th 2020, having originally been planned to take place in Lima, Peru.

This volume presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find numerous contributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational and machine learning methods and estimation techniques. The contributions are focused toward the in vivo recovery of microstructural and connectivity features, as well as combined diffusion-relaxometry acquisitions techniques. This edition includes chapters from high-profile researchers with the specific focus on four topics that are gaining momentum or have received increasing interest within the diffusion MRI community: (i) diffusion MRI signal acquisition, (ii) orientation processing: tractography and visualization, (iii) microstructure modeling and representation, (iv) signal augmentation and super resolution, and (v) diffusion MRI applications.

This volume offers the opportunity to share new perspectives on the most recent research challenges for those currently working in the field, and a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. The book includes rigorous mathematical derivations, a large number of rich, full-color visualizations, and clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics, and applied mathematics.

Each contribution in this volume has been peer-reviewed by multiple members of the international Program Committee. We would like to express our gratitude to all CDMRI20 authors and reviewers for ensuring the quality of the presented work. We are grateful to the MICCAI 2020 chairs for providing a platform to present and discuss the work collected in this volume. We also would like to thank the editors of the Springer book series Mathematics and Visualization as well as Leonie Kunz and Martin Peters (Springer, Heidelberg) for their support to publish this collection as part of their series.