Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Supporting your high street Find out how »
Riemannian Geometric Statistics in Medical Image Analysis, Paperback / softback Book

Riemannian Geometric Statistics in Medical Image Analysis Paperback / softback

Edited by Xavier (National Institute for Research in Computer Science and Control, INRIA, Sophia-Antip Pennec, Stefan (Department of Computer Science, University of Copenhagen) Sommer, Tom (Scientific Computing and Imaging Institute, University of Utah, USA) Fletcher

Paperback / softback

Available to Order - This title is available to order, with delivery expected within 2 weeks

Description

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. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear.

As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces.

The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology 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.

Information

£95.95

Available to Order - This title is available to order, with delivery expected within 2 weeks
Add to Basket
Sign in to add to wishlist
 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information