Riemannian Geometric Statistics in Medical Image Analysis
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Riemannian Geometric Statistics in Medical Image Analysis. / Pennec, Xavier (Editor); Sommer, Stefan Horst (Editor); Fletcher, Tom (Editor).
1. ed. Academic Press, 2020. 636 p.Research output: Book/Report › Book › Research › peer-review
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TY - BOOK
T1 - Riemannian Geometric Statistics in Medical Image Analysis
A2 - Pennec, Xavier
A2 - Sommer, Stefan Horst
A2 - Fletcher, Tom
PY - 2020
Y1 - 2020
N2 - Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data.Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods.
AB - Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data.Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods.
UR - https://www.elsevier.com/books/riemannian-geometric-statistics-in-medical-image-analysis/pennec/978-0-12-814725-2
U2 - 10.1016/C2017-0-01561-6
DO - 10.1016/C2017-0-01561-6
M3 - Book
SN - 9780128147252
BT - Riemannian Geometric Statistics in Medical Image Analysis
PB - Academic Press
ER -
ID: 231753617