Medical Image Analysis
Medical Image Analysis

Author: Alejandro Frangi

Publisher: Academic Press

Published: 2023-09-20

Total Pages: 700

ISBN-13: 0128136588

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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 in Medical Image Analysis
Deep Learning in Medical Image Analysis

Author: Zhengchao Dong

Publisher:

Published: 2021

Total Pages: 458

ISBN-13: 9783036514703

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The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.

Predictive Intelligence in Biomedical and Health Informatics
Predictive Intelligence in Biomedical and Health Informatics

Author: Rajshree Srivastava

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2020-10-12

Total Pages: 180

ISBN-13: 3110676125

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Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Deep Learning for Image Processing Applications
Deep Learning for Image Processing Applications

Author: D.J. Hemanth

Publisher: IOS Press

Published: 2017-12

Total Pages: 284

ISBN-13: 1614998221

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Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.

Image Processing and Analysis with Graphs
Image Processing and Analysis with Graphs

Author: Olivier Lezoray

Publisher: CRC Press

Published: 2017-07-12

Total Pages: 571

ISBN-13: 1351833170

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Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drastic increase in the number of applications based on digital images. This book explores how graphs—which are suitable to represent any discrete data by modeling neighborhood relationships—have emerged as the perfect unified tool to represent, process, and analyze images. It also explains why graphs are ideal for defining graph-theoretical algorithms that enable the processing of functions, making it possible to draw on the rich literature of combinatorial optimization to produce highly efficient solutions. Some key subjects covered in the book include: Definition of graph-theoretical algorithms that enable denoising and image enhancement Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov Random Fields Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets Analysis of the similarity between objects with graph matching Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging Use of graphs has become very influential in computer science and has led to many applications in denoising, enhancement, restoration, and object extraction. Accounting for the wide variety of problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

Conformal and Probabilistic Prediction with Applications
Conformal and Probabilistic Prediction with Applications

Author: Alexander Gammerman

Publisher: Springer

Published: 2016-04-16

Total Pages: 235

ISBN-13: 331933395X

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This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.

Introduction to Biomedical Imaging
Introduction to Biomedical Imaging

Author: Andrew Webb

Publisher: John Wiley & Sons

Published: 2022-11-08

Total Pages: 388

ISBN-13: 1119867711

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Introduction to BiomedicalImaging A state-of-the-art exploration of the foundations and latest developments in biomedical imaging technology In the newly revised second edition of Introduction to Biomedical Imaging, distinguished researcher Dr. Andrew Webb delivers a comprehensive description of the fundamentals and applications of the most important current medical imaging techniques: X-ray and computed tomography, nuclear medicine, ultrasound, magnetic resonance imaging, and various optical-based methods. Each chapter explains the physical principles, instrument design, data acquisition, image reconstruction, and clinical applications of its respective modality. This latest edition incorporates descriptions of recent developments in photon counting CT, total body PET, superresolution-based ultrasound, phased-array MRI technology, optical coherence tomography, and iterative and model-based image reconstruction techniques. The final chapter discusses the increasing role of artificial intelligence/deep learning in biomedical imaging. The text also includes a thorough introduction to general image characteristics, including discussions of signal-to-noise and contrast-to-noise. Perfect for graduate and senior undergraduate students of biomedical engineering, Introduction to Biomedical Imaging, 2nd Edition will also earn a place in the libraries of medical imaging professionals with an interest in medical imaging techniques.

Deep Learning for Medical Image Analysis
Deep Learning for Medical Image Analysis

Author: S. Kevin Zhou

Publisher: Academic Press

Published: 2023-11-23

Total Pages: 544

ISBN-13: 0323858880

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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

Image and Video Processing and Recognition Based on Artificial Intelligence
Image and Video Processing and Recognition Based on Artificial Intelligence

Author: Kang Ryoung Park

Publisher: Mdpi AG

Published: 2023-05-24

Total Pages: 0

ISBN-13: 9783036576022

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This book focuses on challenging issues in the field of AI-based image and video processing and recognition, including the topics of AI-based image processing, understanding, recognition, compression, and reconstruction; AI-based video processing, understanding, recognition, compression, and reconstruction; computer vision based on AI; AI-based biometrics; AI-based object detection and tracking; approaches that combine AI techniques and conventional methods for image and video processing and recognition; explainable AI (XAI) for image and video processing and recognition; generative adversarial network (GAN)-based image and video processing and recognition; and approaches that combine AI techniques and blockchain methods for image and video processing and recognition.

Computer Vision in Sports
Computer Vision in Sports

Author: Thomas B. Moeslund

Publisher: Springer

Published: 2015-01-19

Total Pages: 322

ISBN-13: 3319093967

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The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the players, and identifying the sport being played from video footage. The work concludes by investigating a selection of systems for the automatic analysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.