Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis
Author: Xavier Pennec,Stefan Sommer,Tom Fletcher
Publsiher: Academic Press
Total Pages: 636
Release: 2019-09-02
ISBN 10: 0128147261
ISBN 13: 9780128147269
Language: EN, FR, DE, ES & NL

Riemannian Geometric Statistics in Medical Image Analysis Book Review:

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. 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

Shape in Medical Imaging

Shape in Medical Imaging
Author: Martin Reuter
Publsiher: Springer Nature
Total Pages: 329
Release: 2021
ISBN 10: 303061056X
ISBN 13: 9783030610562
Language: EN, FR, DE, ES & NL

Shape in Medical Imaging Book Review:

Handbook of Medical Image Computing and Computer Assisted Intervention

Handbook of Medical Image Computing and Computer Assisted Intervention
Author: S. Kevin Zhou,Daniel Rueckert,Gabor Fichtinger
Publsiher: Academic Press
Total Pages: 1072
Release: 2019-10-18
ISBN 10: 0128165863
ISBN 13: 9780128165867
Language: EN, FR, DE, ES & NL

Handbook of Medical Image Computing and Computer Assisted Intervention Book Review:

Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. Presents the key research challenges in medical image computing and computer-assisted intervention Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society Contains state-of-the-art technical approaches to key challenges Demonstrates proven algorithms for a whole range of essential medical imaging applications Includes source codes for use in a plug-and-play manner Embraces future directions in the fields of medical image computing and computer-assisted intervention

Computational Retinal Image Analysis

Computational Retinal Image Analysis
Author: Emanuele Trucco,Tom MacGillivray,Yanwu Xu
Publsiher: Academic Press
Total Pages: 502
Release: 2019-11-25
ISBN 10: 0081028172
ISBN 13: 9780081028179
Language: EN, FR, DE, ES & NL

Computational Retinal Image Analysis Book Review:

Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies

Information Processing in Medical Imaging

Information Processing in Medical Imaging
Author: Marc Niethammer,Martin Styner,Stephen Aylward,Hongtu Zhu,Ipek Oguz,Pew-Thian Yap,Dinggang Shen
Publsiher: Springer
Total Pages: 687
Release: 2017-06-06
ISBN 10: 3319590502
ISBN 13: 9783319590509
Language: EN, FR, DE, ES & NL

Information Processing in Medical Imaging Book Review:

This book constitutes the proceedings of the 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, held at the Appalachian State University, Boon, NC, USA, in June 2017. The 53 full papers presented in this volume were carefully reviewed and selected from 147 submissions. They were organized in topical sections named: analysis on manifolds; shape analysis; disease diagnosis/progression; brain networks an connectivity; diffusion imaging; quantitative imaging; imaging genomics; image registration; segmentation; general image analysis.

Algorithmic Advances in Riemannian Geometry and Applications

Algorithmic Advances in Riemannian Geometry and Applications
Author: Hà Quang Minh,Vittorio Murino
Publsiher: Springer
Total Pages: 208
Release: 2016-10-05
ISBN 10: 3319450263
ISBN 13: 9783319450261
Language: EN, FR, DE, ES & NL

Algorithmic Advances in Riemannian Geometry and Applications Book Review:

This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance. This book is not intended to be an encyclopedic compilation of the applications of Riemannian geometry. Instead, it focuses on several important research directions that are currently actively pursued by researchers in the field. These include statistical modeling and analysis on manifolds,optimization on manifolds, Riemannian manifolds and kernel methods, and dictionary learning and sparse coding on manifolds. Examples of applications include novel algorithms for Monte Carlo sampling and Gaussian Mixture Model fitting, 3D brain image analysis,image classification, action recognition, and motion tracking.

Dissertation Abstracts International

Dissertation Abstracts International
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2005
ISBN 10:
ISBN 13: STANFORD:36105121649177
Language: EN, FR, DE, ES & NL

Dissertation Abstracts International Book Review:

Brain Network Analysis

Brain Network Analysis
Author: Moo K. Chung
Publsiher: Cambridge University Press
Total Pages: 320
Release: 2019-06-30
ISBN 10: 110718486X
ISBN 13: 9781107184862
Language: EN, FR, DE, ES & NL

Brain Network Analysis Book Review:

This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis

Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Author: Anonim
Publsiher: IEEE Computer Society
Total Pages: 340
Release: 1996
ISBN 10: 9780818673672
ISBN 13: 0818673672
Language: EN, FR, DE, ES & NL

Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis Book Review:

Thirty-two June 1996 biomedical image workshop papers developing clever computational methods based on geometry, algebra, functional analysis, partial differential equations, optimization and graph theory. Within this mathematical framework the contributors address new and old topics in medical imag

Medical Image Registration

Medical Image Registration
Author: Joseph V. Hajnal,Derek L.G. Hill
Publsiher: CRC Press
Total Pages: 392
Release: 2001-06-27
ISBN 10: 9781420042474
ISBN 13: 1420042475
Language: EN, FR, DE, ES & NL

Medical Image Registration Book Review:

Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared. This is becoming the central tool for image analysis, understanding, and visualization in both medical and scientific applications. Medical Image Registration provid

Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis

Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis
Author: Milan Sonka,Ioannis A. Kakadiaris,Jan Kybic
Publsiher: Springer
Total Pages: 444
Release: 2004-10-04
ISBN 10: 3540278168
ISBN 13: 9783540278160
Language: EN, FR, DE, ES & NL

Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis Book Review:

Medical imaging and medical image analysisare rapidly developing. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. We were enthusiastic when the organizers of the 2004 European Conference on Computer Vision (ECCV) allowed us to organize a satellite workshop devoted to medical image analysis.

Latent Variable Analysis and Signal Separation

Latent Variable Analysis and Signal Separation
Author: Emmanuel Vincent,Arie Yeredor,Zbyněk Koldovský,Petr Tichavský
Publsiher: Springer
Total Pages: 532
Release: 2015-08-14
ISBN 10: 3319224824
ISBN 13: 9783319224824
Language: EN, FR, DE, ES & NL

Latent Variable Analysis and Signal Separation Book Review:

This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.

Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis

Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis
Author: Victor Patrangenaru,Leif Ellingson
Publsiher: CRC Press
Total Pages: 517
Release: 2015-09-18
ISBN 10: 1439820511
ISBN 13: 9781439820513
Language: EN, FR, DE, ES & NL

Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis Book Review:

A New Way of Analyzing Object Data from a Nonparametric Viewpoint Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds. It also presents in-depth applications to practical problems arising in a variety of fields, including statistics, medical imaging, computer vision, pattern recognition, and bioinformatics. The book begins with a survey of illustrative examples of object data before moving to a review of concepts from mathematical statistics, differential geometry, and topology. The authors next describe theory and methods for working on various manifolds, giving a historical perspective of concepts from mathematics and statistics. They then present problems from a wide variety of areas, including diffusion tensor imaging, similarity shape analysis, directional data analysis, and projective shape analysis for machine vision. The book concludes with a discussion of current related research and graduate-level teaching topics as well as considerations related to computational statistics. Researchers in diverse fields must combine statistical methodology with concepts from projective geometry, differential geometry, and topology to analyze data objects arising from non-Euclidean object spaces. An expert-driven guide to this approach, this book covers the general nonparametric theory for analyzing data on manifolds, methods for working with specific spaces, and extensive applications to practical research problems. These problems show how object data analysis opens a formidable door to the realm of big data analysis.

Riemannian Geometry and Geometric Analysis

Riemannian Geometry and Geometric Analysis
Author: Jürgen Jost
Publsiher: Springer Science & Business Media
Total Pages: 535
Release: 2013-03-09
ISBN 10: 3662046725
ISBN 13: 9783662046722
Language: EN, FR, DE, ES & NL

Riemannian Geometry and Geometric Analysis Book Review:

This established reference work continues to lead its readers to some of the hottest topics of contemporary mathematical research. This third edition includes a new presentation of Morse theory and Floer homology. The new material emphasises the geometric aspects and is discussed in the context of Riemannian geometry and geometric analysis. The book also now covers the geometric aspects of harmonic maps, using geometric methods from the theory of geometric spaces of nonpositive curvature. The new material is based on a course at the University of Leipzig. The text is aimed at graduate students and researchers from other areas of mathematics.

Computer Vision in Medical Imaging

Computer Vision in Medical Imaging
Author: C H Chen
Publsiher: World Scientific
Total Pages: 412
Release: 2013-11-18
ISBN 10: 9814460958
ISBN 13: 9789814460958
Language: EN, FR, DE, ES & NL

Computer Vision in Medical Imaging Book Review:

The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs. Contents:An Introduction to Computer Vision in Medical Imaging (Chi Hau Chen)Theory and Methodologies:Distribution Matching Approaches to Medical Image Segmentation (Ismail Ben Ayed)Digital Pathology in Medical Imaging (Bikash Sabata, Chukka Srinivas, Pascal Bamford and Gerardo Fernandez)Adaptive Shape Prior Modeling via Online Dictionary Learning (Shaoting Zhang, Yiqiang Zhan, Yan Zhou and Dimitris Metaxas)Feature-Centric Lesion Detection and Retrieval in Thoracic Images (Yang Song, Weidong Cai, Stefan Eberl, Michael J Fulham and David Dagan Feng)A Novel Paradigm for Quantitation from MR Phase (Joseph Dagher)A Multi-Resolution Active Contour Framework for Ultrasound Image Segmentation (Weiming Wang, Jing Qin, Pheng-Ann Heng, Yim-Pan Chui, Liang Li and Bing Nan Li)2D, 3D Reconstructions/Imaging Algorithms, Systems & Sensor Fusion:Model-Based Image Reconstruction in Optoacoustic Tomography (Amir Rosenthal, Daniel Razansky and Vasilis Ntziachristos)The Fusion of Three-Dimensional Quantitative Coronary Angiography and Intracoronary Imaging for Coronary Interventions (Shengxian Tu, Niels R Holm, Johannes P Janssen and Johan H C Reiber)Three-Dimensional Reconstruction Methods in Near-Field Coded Aperture for SPECT Imaging System (Stephen Baoming Hong)Ultrasound Volume Reconstruction based on Direct Frame Interpolation (Sergei Koptenko, Rachel Remlinger, Martin Lachaine, Tony Falco and Ulrich Scheipers)Deconvolution Technique for Enhancing and Classifying the Retinal Images (Uvais A Qidwai and Umair A Qidwai)Medical Ultrasound Digital Signal Processing in the GPU Computing Era (Marcin Lewandowski)Developing Medical Image Processing Algorithms for GPU Assisted Parallel Computation (Mathias Broxvall and Marios Daotis)Specific Image Processing and Computer Vision Methods for Different Imaging Modalities Including IVUS, MRI, etc.:Computer Vision in Interventional Cardiology (Kendall R Waters)Pattern Classification of Brain Diffusion MRI: Application to Schizophrenia Diagnosis (Ali Tabesh, Matthew J Hoptman, Debra D'Angelo and Babak A Ardekani)On Compressed Sensing Reconstruction for Magnetic Resonance Imaging (Benjamin Paul Berman, Sagar Mandava and Ali Bilgin)On Hierarchical Statistical Shape Models with Application to Brain MRI (Juan J Cerrolaza, Arantxa Villanueva and Rafael Cabeza)Advanced PDE-based Methods for Automatic Quantification of Cardiac Function and Scar from Magnetic Resonance Imaging (Durco Turco and Cristiana Corsi)Automated IVUS Segmentation Using Deformable Template Model with Feature Tracking (Prakash Manandhar and Chi Hau Chen) Readership: Researchers, professionals and academics in machine perception/computer vision, pattern recognition/image analysis, nuclear medicine, bioengineering & cardiology. Keywords:Medical Imaging;Computer Vision;Image Segmentation;Machine Learning;3D InformationKey Features:Uses computer vision techniques for medical imaging dataCovers image processing and segmentation algorithms in intravascular ultrasound, PETscan data, MRI dataEmphaisises 3D information extraction from medical imaging data

Geometric Methods in Bio Medical Image Processing

Geometric Methods in Bio Medical Image Processing
Author: Ravikanth Malladi
Publsiher: Springer Science & Business Media
Total Pages: 147
Release: 2012-12-06
ISBN 10: 3642559875
ISBN 13: 9783642559877
Language: EN, FR, DE, ES & NL

Geometric Methods in Bio Medical Image Processing Book Review:

The genesis of this book goes back to the conference held at the University of Bologna, June 1999, on collaborative work between the University of California at Berkeley and the University of Bologna. The book, in its present form, is a compilation of some of the recent work using geometric partial differential equations and the level set methodology in medical and biomedical image analysis. The book not only gives a good overview on some of the traditional applications in medical imagery such as, CT, MR, Ultrasound, but also shows some new and exciting applications in the area of Life Sciences, such as confocal microscope image understanding.

Medical Image Computing and Computer assisted Intervention

Medical Image Computing and Computer assisted Intervention
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 1998
ISBN 10:
ISBN 13: UOM:39015048112463
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer assisted Intervention Book Review:

Medical Image Computing and Computer Assisted Intervention MICCAI 2008

Medical Image Computing and Computer Assisted Intervention   MICCAI 2008
Author: Dimitris Metaxas,Leon Axel,Gabor Fichtinger,Gabor Szekely
Publsiher: Springer Science & Business Media
Total Pages: 1087
Release: 2008-09-04
ISBN 10: 354085987X
ISBN 13: 9783540859871
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer Assisted Intervention MICCAI 2008 Book Review:

The two-volume set LNCS 5241 and LNCS 5242 constitute the refereed proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008, held in New York, NY, USA, in September 2008. The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.

Guide to Medical Image Analysis

Guide to Medical Image Analysis
Author: Klaus D. Toennies
Publsiher: Springer
Total Pages: 589
Release: 2017-03-29
ISBN 10: 1447173201
ISBN 13: 9781447173205
Language: EN, FR, DE, ES & NL

Guide to Medical Image Analysis Book Review:

This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. This fully updated new edition has been enhanced with material on the latest developments in the field, whilst retaining the original focus on segmentation, classification and registration. Topics and features: presents learning objectives, exercises and concluding remarks in each chapter; describes a range of common imaging techniques, reconstruction techniques and image artifacts, and discusses the archival and transfer of images; reviews an expanded selection of techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation; examines analysis methods in view of image-based guidance in the operating room (NEW); discusses the use of deep convolutional networks for segmentation and labeling tasks (NEW); includes appendices on Markov random field optimization, variational calculus and principal component analysis.

Mathematical Methods for Signal and Image Analysis and Representation

Mathematical Methods for Signal and Image Analysis and Representation
Author: Luc Florack,Remco Duits,Geurt Jongbloed,Marie-Colette van Lieshout,Laurie Davies
Publsiher: Springer Science & Business Media
Total Pages: 320
Release: 2012-01-12
ISBN 10: 1447123530
ISBN 13: 9781447123538
Language: EN, FR, DE, ES & NL

Mathematical Methods for Signal and Image Analysis and Representation Book Review:

Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.