Elisenda Bonet-Carne (ed.); Francesco Grussu (ed.); Lipeng Ning (ed.); Farshid Sepehrband (ed.); Chantal M. W. Tax (ed.) Springer (2019) Kovakantinen kirja
Seyed Mostafa Kia; Hassan Mohy-ud-Din; Ahmed Abdulkadir; Cher Bass; Mohamad Habes; Jane Maryam Rondina; Chantal Tax; Wang Springer Nature Switzerland AG (2020) Pehmeäkantinen kirja
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 methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as frontline applications in neuroscience research and clinical practice.
These proceedings contain the papers presented at the 2017 MICCAI Workshop on Computational Diffusion MRI (CDMRI’17) held in Québec, Canada on September 10, 2017, sharing new perspectives on the most recent research challenges for those currently working in the field, but also offering a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. This book includes rigorous mathematical derivations, a large number of rich, full-colour visualisations 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.
