Medical Image Recognition Segmentation And Parsing

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Medical Image Recognition Segmentation And Parsing

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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2015-12-08

Medical Image Recognition Segmentation And Parsing written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Computers categories.

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms

Medical Image Recognition Segmentation And Parsing

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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2015-12-11

Medical Image Recognition Segmentation And Parsing written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Computers categories.

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: - Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects - Methods and theories for medical image recognition, segmentation and parsing of multiple objects - Efficient and effective machine learning solutions based on big datasets - Selected applications of medical image parsing using proven algorithms - Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects - Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets - Includes algorithms for recognizing and parsing of known anatomies for practical applications

Finite Element Method And Medical Imaging Techniques In Bone Biomechanics

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Author : Rabeb Ben Kahla
language : en
Publisher: John Wiley & Sons
Release Date : 2019-12-05

Finite Element Method And Medical Imaging Techniques In Bone Biomechanics written by Rabeb Ben Kahla and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-05 with Science categories.

Digital models based on data from medical images have recently become widespread in the field of biomechanics. This book summarizes medical imaging techniques and processing procedures, both of which are necessary for creating bone models with finite element methods. Chapter 1 introduces the main principles and the application of the most commonly used medical imaging techniques. Chapter 2 describes the major methods and steps of medical image analysis and processing. Chapter 3 presents a brief review of recent studies on reconstructed finite element bone models, based on medical images. Finally, Chapter 4 reveals the digital results obtained for the main bone sites that have been targeted by finite element modeling in recent years.

Medical Image Analysis

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Author : Alejandro Frangi
language : en
Publisher: Academic Press
Release Date : 2023-09-20

Medical Image Analysis written by Alejandro Frangi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-20 with Technology & Engineering categories.

Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing

Deep Learning For Medical Image Analysis

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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2023-11-23

Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-23 with Computers categories.

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. - Covers common research problems in medical image analysis and their challenges - Describes the latest deep learning methods and the theories behind approaches for medical image analysis - Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment· Includes a Foreword written by Nicholas Ayache

Signal And Image Processing Techniques For The Development Of Intelligent Healthcare Systems

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Author : E. Priya
language : en
Publisher: Springer Nature
Release Date : 2020-09-21

Signal And Image Processing Techniques For The Development Of Intelligent Healthcare Systems written by E. Priya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-21 with Medical categories.

This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.

Handbook Of Medical Image Computing And Computer Assisted Intervention

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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2019-10-18

Handbook Of Medical Image Computing And Computer Assisted Intervention written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Computers categories.

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

Trustworthy Ai In Medical Imaging

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Author : Marco Lorenzi
language : en
Publisher: Elsevier
Release Date : 2024-11-25

Trustworthy Ai In Medical Imaging written by Marco Lorenzi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-25 with Computers categories.

Trustworthy AI in Medical Imaging brings together scientific researchers, medical experts, and industry partners working in the field of trustworthiness, bridging the gap between AI research and concrete medical applications and making it a learning resource for undergraduates, masters students, and researchers in AI for medical imaging applications. The book will help readers acquire the basic notions of AI trustworthiness and understand its concrete application in medical imaging, identify pain points and solutions to enhance trustworthiness in medical imaging applications, understand current limitations and perspectives of trustworthy AI in medical imaging, and identify novel research directions. Although the problem of trustworthiness in AI is actively researched in different disciplines, the adoption and implementation of trustworthy AI principles in real-world scenarios is still at its infancy. This is particularly true in medical imaging where guidelines and standards for trustworthiness are critical for the successful deployment in clinical practice. After setting out the technical and clinical challenges of AI trustworthiness, the book gives a concise overview of the basic concepts before presenting state-of-the-art methods for solving these challenges. - Introduces the key concepts of trustworthiness in AI. - Presents state-of-the-art methodologies for trustworthy AI in medical imaging. - Outlines major initiatives focusing on real-world deployment of trustworthy principles in medical imaging applications. - Presents outstanding questions still to be solved and discusses future research directions.

Riemannian Geometric Statistics In Medical Image Analysis

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Author : Xavier Pennec
language : en
Publisher: Academic Press
Release Date : 2019-09-04

Riemannian Geometric Statistics In Medical Image Analysis written by Xavier Pennec and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-04 with Computers categories.

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.

Deep Network Design For Medical Image Computing

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Author : Haofu Liao
language : en
Publisher: Academic Press
Release Date : 2022-08-24

Deep Network Design For Medical Image Computing written by Haofu Liao and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-24 with Computers categories.

Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc. For each topic, the book provides a deep learning-based solution that takes into account the medical or biological aspect of the problem and how the solution addresses a variety of important questions surrounding architecture, the design of deep learning techniques, when to introduce adversarial learning, and more. This book will help graduate students and researchers develop a better understanding of the deep learning design principles for MIC and to apply them to their medical problems. - Explains design principles of deep learning techniques for MIC - Contains cutting-edge deep learning research on MIC - Covers a broad range of MIC tasks, including the classification, detection, segmentation, registration, reconstruction and synthesis of medical images