Medical Image Recognition Segmentation And Parsing

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Medical Image Recognition, Segmentation and Parsing

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0128026766
Total Pages : 542 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou

Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-11 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Medical Image Recognition, Segmentation and Parsing

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 9780128025819
Total Pages : 0 pages
Book Rating : 4.0/5 (258 download)

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Book Synopsis Medical Image Recognition, Segmentation and Parsing by : S. Kevin Zhou

Download or read book Medical Image Recognition, Segmentation and Parsing written by S. Kevin Zhou and published by Academic Press. This book was released on 2015-12-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Deep Learning for Medical Image Analysis

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0323858880
Total Pages : 544 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Medical Computer Vision

Author : Bjoern Menze
Publisher : Springer
ISBN 13 : 3642184219
Total Pages : 226 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Medical Computer Vision by : Bjoern Menze

Download or read book Medical Computer Vision written by Bjoern Menze and published by Springer. This book was released on 2011-02-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2010, held in Beijing, China, in September 2010 as a satellite event of the 13th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2010. The 10 revised full papers and 11 revised poster papers presented were carefully reviewed and selected from 38 initial submissions. The papers explore the use of modern image recognition technology in tasks such as semantic anatomy parsing, automatic segmentation and quantification, anomaly detection and categorization, data harvesting, semantic navigation and visualization, data organization and clustering, and general-purpose automatic understanding of medical images.

Medical Imaging

Author : K.C. Santosh
Publisher : CRC Press
ISBN 13 : 0429639325
Total Pages : 200 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Medical Imaging by : K.C. Santosh

Download or read book Medical Imaging written by K.C. Santosh and published by CRC Press. This book was released on 2019-08-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

MEDICAL IMAGE PROCESSING

Author : G.R. SINHA
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 8120349024
Total Pages : 268 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis MEDICAL IMAGE PROCESSING by : G.R. SINHA

Download or read book MEDICAL IMAGE PROCESSING written by G.R. SINHA and published by PHI Learning Pvt. Ltd.. This book was released on 2014-01-20 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Processing: Concepts and Applications presents an overview of image processing for various applications in the field of medical science. Inclusion of several topics like noise reduction filters, feature extraction, image restoration, segmentation, soft computing techniques and context-based medical image retrieval, etc. makes this book a single-source information meeting the requirements of the readers. Besides, the coverage of digital image processing, human visual perception and CAD system to be used in automated diagnosis system, medical imaging modalities, various application areas of medical field, detection and classification of various disease, etc. is highly emphasised in the book. The book, divided into eight chapters, presents the topics in a clear, simple, practical and cogent fashion that provides the students with the insight into theory as well as applications to the practical problems. The research orientation of the book greatly supports the concepts of image processing to be applied for segmentation, classification and detection of affected areas in X-ray, MRI and mammographic and all other medical images. Throughout the book, an attempt has been made to address the challenges faced by radiologists, physicians and doctors in scanning, interpretation and diagnosis process. The book uses an abundance of colour images to impart a high level of comprehension of concepts and helps in mastering the process of medical image processing. Special attention is made on the review of algorithms or methods of medical image formation, processing and analysis, medical imaging applications, and emerging medical imaging modality. This is purely a text dedicated for the undergraduate and postgraduate students of biomedical engineering. The book is also of immense use to the students of computer science engineering and IT who offer a course on digital image processing. Key Points • Chapter-end review questions test the students’ knowledge of the funda-mental concepts. • Course outcomes help the students in capturing the key points. • Several images and information regarding morphological operations given in appendices help in getting additional knowledge in the field of medical image processing.

Guide to Medical Image Analysis

Author : Klaus D. Toennies
Publisher : Springer
ISBN 13 : 1447173201
Total Pages : 589 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Guide to Medical Image Analysis by : Klaus D. Toennies

Download or read book Guide to Medical Image Analysis written by Klaus D. Toennies and published by Springer. This book was released on 2017-03-29 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Medical Image Analysis

Author : Alejandro Frangi
Publisher : Academic Press
ISBN 13 : 0128136588
Total Pages : 700 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Medical Image Analysis by : Alejandro Frangi

Download or read book Medical Image Analysis written by Alejandro Frangi and published by Academic Press. This book was released on 2023-09-20 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Provides an authoritative description of key concepts and methods Includes tutorial-based sections that clearly explain principles and their application to different medical domains Presents a representative selection of topics to match a modern and relevant approach to medical image computing

Medical Image Processing

Author : Geoff Dougherty
Publisher : Springer Science & Business Media
ISBN 13 : 9781441997791
Total Pages : 380 pages
Book Rating : 4.9/5 (977 download)

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Book Synopsis Medical Image Processing by : Geoff Dougherty

Download or read book Medical Image Processing written by Geoff Dougherty and published by Springer Science & Business Media. This book was released on 2011-07-25 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to ensure conceptual learning before introducing specific techniques and “tricks of the trade”. The book concentrates on a number of current research applications, and will present a detailed approach to each while emphasizing the applicability of techniques to other problems. The field of topics is wide, ranging from compressive (non-uniform) sampling in MRI, through automated retinal vessel analysis to 3-D ultrasound imaging and more. The book is amply illustrated with figures and applicable medical images. The reader will learn the techniques which experts in the field are currently employing and testing to solve particular research problems, and how they may be applied to other problems.

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Author : Ben Othman Soufiene
Publisher : CRC Press
ISBN 13 : 1003805671
Total Pages : 270 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning and Deep Learning Techniques for Medical Image Recognition by : Ben Othman Soufiene

Download or read book Machine Learning and Deep Learning Techniques for Medical Image Recognition written by Ben Othman Soufiene and published by CRC Press. This book was released on 2023-12-01 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.

Deep Learning in Medical Image Analysis

Author : Gobert Lee
Publisher : Springer Nature
ISBN 13 : 3030331288
Total Pages : 184 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Deep Learning in Medical Image Analysis by : Gobert Lee

Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

Advanced Algorithmic Approaches to Medical Image Segmentation

Author : S. Kamaledin Setarehdan
Publisher : Springer Science & Business Media
ISBN 13 : 0857293338
Total Pages : 661 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Advanced Algorithmic Approaches to Medical Image Segmentation by : S. Kamaledin Setarehdan

Download or read book Advanced Algorithmic Approaches to Medical Image Segmentation written by S. Kamaledin Setarehdan and published by Springer Science & Business Media. This book was released on 2012-09-07 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging is an important topic and plays a key role in robust diagnosis and patient care. It has experienced an explosive growth over the last few years due to imaging modalities such as X-rays, computed tomography (CT), magnetic resonance (MR) imaging, and ultrasound. This book focuses primarily on model-based segmentation techniques, which are applied to cardiac, brain, breast and microscopic cancer cell imaging. It includes contributions from authors working in industry and academia, and presents new material.

Deep Learning and Convolutional Neural Networks for Medical Image Computing

Author : Le Lu
Publisher : Springer
ISBN 13 : 331942999X
Total Pages : 326 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Image Computing by : Le Lu

Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Biomedical Image Segmentation

Author : Ayman El-Baz
Publisher : CRC Press
ISBN 13 : 1482258560
Total Pages : 547 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Biomedical Image Segmentation by : Ayman El-Baz

Download or read book Biomedical Image Segmentation written by Ayman El-Baz and published by CRC Press. This book was released on 2016-11-17 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Author : Le Lu
Publisher : Springer Nature
ISBN 13 : 3030139697
Total Pages : 461 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics by : Le Lu

Download or read book Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics written by Le Lu and published by Springer Nature. This book was released on 2019-09-19 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval. The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

Decision Forests for Computer Vision and Medical Image Analysis

Author : Antonio Criminisi
Publisher : Springer Science & Business Media
ISBN 13 : 1447149297
Total Pages : 367 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Decision Forests for Computer Vision and Medical Image Analysis by : Antonio Criminisi

Download or read book Decision Forests for Computer Vision and Medical Image Analysis written by Antonio Criminisi and published by Springer Science & Business Media. This book was released on 2013-01-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Author : Danail Stoyanov
Publisher : Springer
ISBN 13 : 3030008894
Total Pages : 401 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support by : Danail Stoyanov

Download or read book Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support written by Danail Stoyanov and published by Springer. This book was released on 2018-09-19 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.