Riemannian Geometric Statistics in Medical Image Analysis
  • Author : Xavier Pennec
  • Release Date : 01 September 2019
  • Publisher : Academic Press
  • Genre : Computers
  • Pages : 636
  • ISBN 13 : 9780128147252

Riemannian Geometric Statistics in Medical Image Analysis Book Summary

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. Content includes: - The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs - Applications of statistics on manifolds and shape spaces in medical image computing - Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science. - A complete reference covering both the foundations and state-of-the-art methods - Edited and authored by leading researchers in the field - Contains theory, examples, applications, and algorithms - Gives an overview of current research challenges and future applications

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis

Author : Xavier Pennec,Stefan Sommer,Tom Fletcher
Publisher : Academic Press
Genre : Computers
Total View : 7355 Views
File Size : 41,9 Mb
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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 ...

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis

Author : Xavier Pennec,Stefan Sommer,Tom Fletcher
Publisher : Academic Press
Genre : Computers
Total View : 9584 Views
File Size : 43,5 Mb
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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 ...

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Publisher : Springer Nature
Genre : Computers
Total View : 3954 Views
File Size : 54,9 Mb
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This book offers readers fresh insights on applying Extended Reality to Digital Anatomy, a novel emerging discipline. Indeed, the way professors teach anatomy in classrooms is changing rapidly as novel technology-based approaches become ever more accessible. Recent studies show that Virtual (VR), Augmented (AR), and Mixed-Reality (MR) can improve both ...

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Genre : Mathematics
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Publisher : CRC Press
Genre : Computers
Total View : 3870 Views
File Size : 55,7 Mb
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Object Oriented Data Analysis is a framework that facilitates inter-disciplinary research through new terminology for discussing the often many possible approaches to the analysis of complex data. Such data are naturally arising in a wide variety of areas. This book aims to provide ways of thinking that enable the making ...