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

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
ISBN 10: 0128147253
ISBN 13: 9780128147252
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. 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

Digital Anatomy

Digital Anatomy
Author: Jean-François Uhl,Joaquim Jorge,Daniel Simões Lopes,Pedro F. Campos
Publsiher: Springer Nature
Total Pages: 385
Release: 2021-05-14
ISBN 10: 3030619052
ISBN 13: 9783030619053
Language: EN, FR, DE, ES & NL

Digital Anatomy Book Review:

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 retention and learning outcomes. Readers will find relevant tutorials about three-dimensional reconstruction techniques to perform virtual dissections. Several chapters serve as practical manuals for students and trainers in anatomy to refresh or develop their Digital Anatomy skills. We developed this book as a support tool for collaborative efforts around Digital Anatomy, especially in distance learning, international and interdisciplinary contexts. We aim to leverage source material in this book to support new Digital Anatomy courses and syllabi in interdepartmental, interdisciplinary collaborations. Digital Anatomy – Applications of Virtual, Mixed and Augmented Reality provides a valuable tool to foster cross-disciplinary dialogues between anatomists, surgeons, radiologists, clinicians, computer scientists, course designers, and industry practitioners. It is the result of a multidisciplinary exercise and will undoubtedly catalyze new specialties and collaborative Master and Doctoral level courses world-wide. In this perspective, the UNESCO Chair in digital anatomy was created at the Paris Descartes University in 2015 (www.anatomieunesco.org). It aims to federate the education of anatomy around university partners from all over the world, wishing to use these new 3D modeling techniques of the human body.

Shape in Medical Imaging

Shape in Medical Imaging
Author: Martin Reuter
Publsiher: Springer Nature
Total Pages: 135
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

Medical Image Computing and Computer Assisted Intervention MICCAI 2021

Medical Image Computing and Computer Assisted Intervention     MICCAI 2021
Author: Marleen de Bruijne
Publsiher: Springer Nature
Total Pages: 135
Release: 2021
ISBN 10: 3030872319
ISBN 13: 9783030872311
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer Assisted Intervention MICCAI 2021 Book Review:

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

Object Oriented Data Analysis

Object Oriented Data Analysis
Author: J. S. Marron,Ian L. Dryden
Publsiher: CRC Press
Total Pages: 436
Release: 2021-11-18
ISBN 10: 1351189662
ISBN 13: 9781351189668
Language: EN, FR, DE, ES & NL

Object Oriented Data Analysis Book Review:

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 of sensible choices. The main points are illustrated with many real data examples, based on the authors' personal experiences, which have motivated the invention of a wide array of analytic methods. While the mathematics go far beyond the usual in statistics (including differential geometry and even topology), the book is aimed at accessibility by graduate students. There is deliberate focus on ideas over mathematical formulas. J. S. Marron is the Amos Hawley Distinguished Professor of Statistics, Professor of Biostatistics, Adjunct Professor of Computer Science, Faculty Member of the Bioinformatics and Computational Biology Curriculum and Research Member of the Lineberger Cancer Center and the Computational Medicine Program, at the University of North Carolina, Chapel Hill. Ian L. Dryden is a Professor in the Department of Mathematics and Statistics at Florida International University in Miami, has served as Head of School of Mathematical Sciences at the University of Nottingham, and is joint author of the acclaimed book Statistical Shape Analysis.

Information Processing in Medical Imaging

Information Processing in Medical Imaging
Author: Aasa Feragen,Stefan Sommer,Julia Schnabel,Mads Nielsen
Publsiher: Springer Nature
Total Pages: 782
Release: 2021-06-20
ISBN 10: 3030781917
ISBN 13: 9783030781910
Language: EN, FR, DE, ES & NL

Information Processing in Medical Imaging Book Review:

This book constitutes the proceedings of the 27th International Conference on Information Processing in Medical Imaging, IPMI 2021, which was held online during June 28-30, 2021. The conference was originally planned to take place in Bornholm, Denmark, but changed to a virtual format due to the COVID-19 pandemic. The 59 full papers presented in this volume were carefully reviewed and selected from 200 submissions. They were organized in topical sections as follows: registration; causal models and interpretability; generative modelling; shape; brain connectivity; representation learning; segmentation; sequential modelling; learning with few or low quality labels; uncertainty quantification and generative modelling; and deep learning.

Processing Analyzing and Learning of Images Shapes and Forms

Processing  Analyzing and Learning of Images  Shapes  and Forms
Author: Xue-Cheng Tai
Publsiher: North Holland
Total Pages: 525
Release: 2019-10
ISBN 10: 0444641408
ISBN 13: 9780444641403
Language: EN, FR, DE, ES & NL

Processing Analyzing and Learning of Images Shapes and Forms Book Review:

Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more. Covers contemporary developments relating to the analysis and learning of images, shapes and forms Presents mathematical models and quick computational techniques relating to the topic Provides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods

Processing Analyzing and Learning of Images Shapes and Forms Part 2

Processing  Analyzing and Learning of Images  Shapes  and Forms  Part 2
Author: Anonim
Publsiher: Elsevier
Total Pages: 706
Release: 2019-10-16
ISBN 10: 0444641416
ISBN 13: 9780444641410
Language: EN, FR, DE, ES & NL

Processing Analyzing and Learning of Images Shapes and Forms Part 2 Book Review:

Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more. Covers contemporary developments relating to the analysis and learning of images, shapes and forms Presents mathematical models and quick computational techniques relating to the topic Provides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods

Medical Image Computing and Computer Assisted Intervention MICCAI 2010

Medical Image Computing and Computer Assisted Intervention    MICCAI 2010
Author: Tianzi Jiang,Nassir Navab,Josien P.W. Pluim,Max A. Viergever
Publsiher: Springer Science & Business Media
Total Pages: 709
Release: 2010-09
ISBN 10: 3642157041
ISBN 13: 9783642157042
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer Assisted Intervention MICCAI 2010 Book Review:

The three-volume set LNCS 6361, 6362 and 6363 constitutes the refereed proceedings of the 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, held in Beijing, China, in September 2010. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 786 submissions for presentation in three volumes. The first volume includes 84 papers organized in topical sections on computer-aided diagnosis, planning and guidance of interventions, image segmentation, image reconstruction and restoration, functional and diffusion-weighted MRI, modeling and simulation, instrument and patient localization and tracking, quantitative image analysis, image registration, computational and interventional cardiology, and diffusion tensor MR imaging and analysis.

Geometric Science of Information

Geometric Science of Information
Author: Frank Nielsen,Frédéric Barbaresco
Publsiher: Springer Nature
Total Pages: 135
Release: 2021
ISBN 10: 3030802094
ISBN 13: 9783030802097
Language: EN, FR, DE, ES & NL

Geometric Science of Information Book Review:

This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021. The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.

Radiomics and Its Clinical Application

Radiomics and Its Clinical Application
Author: Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei
Publsiher: Academic Press
Total Pages: 300
Release: 2021-06-18
ISBN 10: 0128181028
ISBN 13: 9780128181027
Language: EN, FR, DE, ES & NL

Radiomics and Its Clinical Application Book Review:

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice. An introduction to the concepts of radiomics In-depth presentation of the core technologies and methods Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms

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.

Statistics and Analysis of Shapes

Statistics and Analysis of Shapes
Author: Hamid Krim,Anthony Yezzi
Publsiher: Springer Science & Business Media
Total Pages: 396
Release: 2007-12-31
ISBN 10: 9780817644819
ISBN 13: 0817644814
Language: EN, FR, DE, ES & NL

Statistics and Analysis of Shapes Book Review:

The subject of pattern analysis and recognition pervades many aspects of our daily lives, including user authentication in banking, object retrieval from databases in the consumer sector, and the omnipresent surveillance and security measures around sensitive areas. Shape analysis, a fundamental building block in many approaches to these applications, is also used in statistics, biomedical applications (Magnetic Resonance Imaging), and many other related disciplines. With contributions from some of the leading experts and pioneers in the field, this self-contained, unified volume is the first comprehensive treatment of theory, methods, and algorithms available in a single resource. Developments are discussed from a rapidly increasing number of research papers in diverse fields, including the mathematical and physical sciences, engineering, and medicine.

Brain Body and Machine

Brain  Body and Machine
Author: Jorge Angeles,Benoit Boulet,James J. Clark,Jozsef Kovecses,Kaleem Siddiqi
Publsiher: Springer Science & Business Media
Total Pages: 327
Release: 2010-10-01
ISBN 10: 9783642162596
ISBN 13: 3642162592
Language: EN, FR, DE, ES & NL

Brain Body and Machine Book Review:

The reader will find here papers on human-robot interaction as well as human safety algorithms; haptic interfaces; innovative instruments and algorithms for the sensing of motion and the identification of brain neoplasms; even a paper on a saxophone-playing robot.

Medical Image Computing and Computer Assisted Intervention MICCAI 2016

Medical Image Computing and Computer Assisted Intervention   MICCAI 2016
Author: Sebastien Ourselin,Leo Joskowicz,Mert R. Sabuncu,Gozde Unal,William Wells
Publsiher: Springer
Total Pages: 641
Release: 2016-10-17
ISBN 10: 3319467263
ISBN 13: 9783319467269
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer Assisted Intervention MICCAI 2016 Book Review:

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis, brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR image analysis.

Computational Vision and Medical Image Processing

Computational Vision and Medical Image Processing
Author: Joao Tavares,R. M. Natal Jorge
Publsiher: Springer Science & Business Media
Total Pages: 349
Release: 2010-11-22
ISBN 10: 9400700113
ISBN 13: 9789400700116
Language: EN, FR, DE, ES & NL

Computational Vision and Medical Image Processing Book Review:

This book contains extended versions of papers presented at the international Conference VIPIMAGE 2009 – ECCOMAS Thematic Conference on Computational Vision and Medical Image, that was held at Faculdade de Engenharia da Universidade do Porto, Portugal, from 14th to 16th of October 2009. This conference was the second ECCOMAS thematic conference on computational vision and medical image processing. It covered topics related to image processing and analysis, medical imaging and computational modelling and simulation, considering their multidisciplinary nature. The book collects the state-of-the-art research, methods and new trends on the subject of computational vision and medical image processing contributing to the development of these knowledge areas.

Machine Learning in Computer Aided Diagnosis Medical Imaging Intelligence and Analysis

Machine Learning in Computer Aided Diagnosis  Medical Imaging Intelligence and Analysis
Author: Suzuki, Kenji
Publsiher: IGI Global
Total Pages: 524
Release: 2012-01-31
ISBN 10: 1466600608
ISBN 13: 9781466600607
Language: EN, FR, DE, ES & NL

Machine Learning in Computer Aided Diagnosis Medical Imaging Intelligence and Analysis Book Review:

"This book provides a comprehensive overview of machine learning research and technology in medical decision-making based on medical images"--Provided by publisher.