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.

Medical Image Analysis

Medical Image Analysis
Author: Atam P. Dhawan
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2011-03-29
ISBN 10: 0470922893
ISBN 13: 9780470922897
Language: EN, FR, DE, ES & NL

Medical Image Analysis Book Review:

The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter. A new chapter on Optical Imaging Modalities elaborating microscopy, confocal microscopy, endoscopy, optical coherent tomography, fluorescence and molecular imaging will be added. Another new chapter on Simultaneous Multi-Modality Medical Imaging including CT-SPECT and CT-PET will also be added. In the image analysis part, chapters on image reconstructions and visualizations will be significantly enhanced to include, respectively, 3-D fast statistical estimation based reconstruction methods, and 3-D image fusion and visualization overlaying multi-modality imaging and information. A new chapter on Computer-Aided Diagnosis and image guided surgery, and surgical and therapeutic intervention will also be added. A companion site containing power point slides, author biography, corrections to the first edition and images from the text can be found here: ftp://ftp.wiley.com/public/sci_tech_med/medical_image/ Send an email to: [email protected] to obtain a solutions manual. Please include your affiliation in your email.

Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
Author: S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publsiher: Academic Press
Total Pages: 458
Release: 2017-01-18
ISBN 10: 0128104090
ISBN 13: 9780128104095
Language: EN, FR, DE, ES & NL

Deep Learning for Medical Image Analysis Book Review:

Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Introduction to Medical Image Analysis

Introduction to Medical Image Analysis
Author: Rasmus R. Paulsen,Thomas B. Moeslund
Publsiher: Springer
Total Pages: 186
Release: 2020-05-27
ISBN 10: 9783030393632
ISBN 13: 3030393631
Language: EN, FR, DE, ES & NL

Introduction to Medical Image Analysis Book Review:

This easy-to-follow textbook presents an engaging introduction to the fascinating world of medical image analysis. Avoiding an overly mathematical treatment, the text focuses on intuitive explanations, illustrating the key algorithms and concepts in a way which will make sense to students from a broad range of different backgrounds. Topics and features: explains what light is, and how it can be captured by a camera and converted into an image, as well as how images can be compressed and stored; describes basic image manipulation methods for understanding and improving image quality, and a useful segmentation algorithm; reviews the basic image processing methods for segmenting or enhancing certain features in an image, with a focus on morphology methods for binary images; examines how to detect, describe, and recognize objects in an image, and how the nature of color can be used for segmenting objects; introduces a statistical method to determine what class of object the pixels in an image represent; describes how to change the geometry within an image, how to align two images so that they are as similar as possible, and how to detect lines and paths in images; provides further exercises and other supplementary material at an associated website. This concise and accessible textbook will be invaluable to undergraduate students of computer science, engineering, medicine, and any multi-disciplinary courses that combine topics on health with data science. Medical practitioners working with medical imaging devices will also appreciate this easy-to-understand explanation of the technology.

Biomedical Image Analysis

Biomedical Image Analysis
Author: Rangaraj M. Rangayyan
Publsiher: CRC Press
Total Pages: 1312
Release: 2004-12-30
ISBN 10: 0203492544
ISBN 13: 9780203492543
Language: EN, FR, DE, ES & NL

Biomedical Image Analysis Book Review:

Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges. Biomedical Image Analysis demonstr

Medical Image Processing

Medical Image Processing
Author: Geoff Dougherty
Publsiher: Springer Science & Business Media
Total Pages: 380
Release: 2011-07-25
ISBN 10: 9781441997791
ISBN 13: 1441997792
Language: EN, FR, DE, ES & NL

Medical Image Processing Book Review:

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.

Handbook of Medical Imaging

Handbook of Medical Imaging
Author: Anonim
Publsiher: Academic Press
Total Pages: 901
Release: 2000-10-09
ISBN 10: 9780080533100
ISBN 13: 0080533108
Language: EN, FR, DE, ES & NL

Handbook of Medical Imaging Book Review:

In recent years, the remarkable advances in medical imaging instruments have increased their use considerably for diagnostics as well as planning and follow-up of treatment. Emerging from the fields of radiology, medical physics and engineering, medical imaging no longer simply deals with the technology and interpretation of radiographic images. The limitless possibilities presented by computer science and technology, coupled with engineering advances in signal processing, optics and nuclear medicine have created the vastly expanded field of medical imaging. The Handbook of Medical Imaging is the first comprehensive compilation of the concepts and techniques used to analyze and manipulate medical images after they have been generated or digitized. The Handbook is organized in six sections that relate to the main functions needed for processing: enhancement, segmentation, quantification, registration, visualization as well as compression storage and telemedicine. * Internationally renowned authors(Johns Hopkins, Harvard, UCLA, Yale, Columbia, UCSF) * Includes imaging and visualization * Contains over 60 pages of stunning, four-color images

Medical and Biological Image Analysis

Medical and Biological Image Analysis
Author: Anonim
Publsiher: BoD – Books on Demand
Total Pages: 134
Release: 2018-07-04
ISBN 10: 1789233305
ISBN 13: 9781789233308
Language: EN, FR, DE, ES & NL

Medical and Biological Image Analysis Book Review:

This book deals with medical image analysis methods. In particular, it contains two significant chapters on image segmentation as well as some selected examples of the application of image analysis and processing methods. Despite the significant development of information technology methods used in modern image analysis and processing algorithms, the segmentation process remains open. This is mainly due to intra-patient variability and/or scene diversity. Segmentation is equally difficult in the case of ultrasound imaging and depends on the location of the probe or the contact force. Regardless of the imaging method, segmentation must be tailored for a specific application in almost every case. These types of application areas for various imaging methods are included in this book.

Medical Image Analysis

Medical Image Analysis
Author: Alejandro F. Frangi,Jerry L. Prince,Milan Sonka
Publsiher: Academic Press
Total Pages: 935
Release: 2019-02-15
ISBN 10: 9780128136577
ISBN 13: 012813657X
Language: EN, FR, DE, ES & NL

Medical Image Analysis Book Review:

Medical imaging is increasingly at the base of many fundamental breakthroughs in biomedical sciences, becoming a fundamental enabling technology of biomedical scientific progress. This book presents practical knowledge on medical image computing and analysis Written by top educators and experts in the field, this text is a modern, practical, broad, and self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains, reflecting the nature of the discipline today. Learn: The core representations and properties of digital images and image enhancement techniques Advanced image computing methods including segmentation, registration, motion and shape analysis, and machine learning How medical image computing (MIC) is used in clinical and medical research How to identify alternative strategies and employ software tools to solve typical problems in MIC An authoritative description of key concepts and methods Tutorial-based sections that clearly explain the principles and their application to different medical domains Self-contained chapters provide flexibility, allowing the text to be used on courses with different structures A representative selection of topics to match a modern and relevant approach to medical image computing Focus on medical image computing as a technology to meet clinical needs

Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis
Author: Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey
Publsiher: Academic Press
Total Pages: 308
Release: 2020-08-11
ISBN 10: 0128192968
ISBN 13: 9780128192962
Language: EN, FR, DE, ES & NL

Advanced Machine Vision Paradigms for Medical Image Analysis Book Review:

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

Ophthalmic Medical Image Analysis

Ophthalmic Medical Image Analysis
Author: Huazhu Fu,Mona K. Garvin,Tom MacGillivray,Yanwu Xu,Yalin Zheng
Publsiher: Springer
Total Pages: 192
Release: 2019-10-18
ISBN 10: 9783030329556
ISBN 13: 3030329550
Language: EN, FR, DE, ES & NL

Ophthalmic Medical Image Analysis Book Review:

This book constitutes the refereed proceedings of the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 22 full papers (out of 36 submissions) presented at OMIA 2019 were carefully reviewed and selected. The papers cover various topics in the field of ophthalmic image analysis.

Color Medical Image Analysis

Color Medical Image Analysis
Author: M. Emre Celebi,Gerald Schaefer
Publsiher: Springer Science & Business Media
Total Pages: 206
Release: 2012-09-16
ISBN 10: 9400753896
ISBN 13: 9789400753891
Language: EN, FR, DE, ES & NL

Color Medical Image Analysis Book Review:

Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.

Deep Learning in Medical Image Analysis

Deep Learning in Medical Image Analysis
Author: Gobert Lee,Hiroshi Fujita
Publsiher: Springer Nature
Total Pages: 181
Release: 2020-02-06
ISBN 10: 3030331288
ISBN 13: 9783030331283
Language: EN, FR, DE, ES & NL

Deep Learning in Medical Image Analysis Book Review:

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.

Medical Image Analysis Methods

Medical Image Analysis Methods
Author: Lena Costaridou
Publsiher: CRC Press
Total Pages: 504
Release: 2005-07-13
ISBN 10: 9780203500453
ISBN 13: 0203500458
Language: EN, FR, DE, ES & NL

Medical Image Analysis Methods Book Review:

To successfully detect and diagnose disease, it is vital for medical diagnosticians to properly apply the latest medical imaging technologies. It is a worrisome reality that due to either the nature or volume of some of the images provided, early or obscured signs of disease can go undetected or be misdiagnosed. To combat these inaccuracies, diagno

Medical Image Analysis and Informatics

Medical Image Analysis and Informatics
Author: Paulo Mazzoncini de Azevedo-Marques,Arianna Mencattini,Marcello Salmeri,Rangaraj M. Rangayyan
Publsiher: CRC Press
Total Pages: 518
Release: 2017-11-23
ISBN 10: 1498753205
ISBN 13: 9781498753203
Language: EN, FR, DE, ES & NL

Medical Image Analysis and Informatics Book Review:

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image generation, processing, visualization, archival, transmission, modeling, and analysis has grown substantially. Computers are being integrated into almost every medical imaging system. Medical Image Analysis and Informatics demonstrates how quantitative analysis becomes possible by the application of computational procedures to medical images. Furthermore, it shows how quantitative and objective analysis facilitated by medical image informatics, CBIR, and CAD could lead to improved diagnosis by physicians. Whereas CAD has become a part of the clinical workflow in the detection of breast cancer with mammograms, it is not yet established in other applications. CBIR is an alternative and complementary approach for image retrieval based on measures derived from images, which could also facilitate CAD. This book shows how digital image processing techniques can assist in quantitative analysis of medical images, how pattern recognition and classification techniques can facilitate CAD, and how CAD systems can assist in achieving efficient diagnosis, in designing optimal treatment protocols, in analyzing the effects of or response to treatment, and in clinical management of various conditions. The book affirms that medical imaging, medical image analysis, medical image informatics, CBIR, and CAD are proven as well as essential techniques for health care.

Handbook of Medical Image Processing and Analysis

Handbook of Medical Image Processing and Analysis
Author: Isaac Bankman
Publsiher: Elsevier
Total Pages: 1000
Release: 2008-12-24
ISBN 10: 9780080559148
ISBN 13: 008055914X
Language: EN, FR, DE, ES & NL

Handbook of Medical Image Processing and Analysis Book Review:

The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and analyzing medical images after they have been generated or digitized. The Handbook is organized into six sections that relate to the main functions: enhancement, segmentation, quantification, registration, visualization, and compression, storage and communication. The second edition is extensively revised and updated throughout, reflecting new technology and research, and includes new chapters on: higher order statistics for tissue segmentation; tumor growth modeling in oncological image analysis; analysis of cell nuclear features in fluorescence microscopy images; imaging and communication in medical and public health informatics; and dynamic mammogram retrieval from web-based image libraries. For those looking to explore advanced concepts and access essential information, this second edition of Handbook of Medical Image Processing and Analysis is an invaluable resource. It remains the most complete single volume reference for biomedical engineers, researchers, professionals and those working in medical imaging and medical image processing. Dr. Isaac N. Bankman is the supervisor of a group that specializes on imaging, laser and sensor systems, modeling, algorithms and testing at the Johns Hopkins University Applied Physics Laboratory. He received his BSc degree in Electrical Engineering from Bogazici University, Turkey, in 1977, the MSc degree in Electronics from University of Wales, Britain, in 1979, and a PhD in Biomedical Engineering from the Israel Institute of Technology, Israel, in 1985. He is a member of SPIE. Includes contributions from internationally renowned authors from leading institutions NEW! 35 of 56 chapters have been revised and updated. Additionally, five new chapters have been added on important topics incluling Nonlinear 3D Boundary Detection, Adaptive Algorithms for Cancer Cytological Diagnosis, Dynamic Mammogram Retrieval from Web-Based Image Libraries, Imaging and Communication in Health Informatics and Tumor Growth Modeling in Oncological Image Analysis. Provides a complete collection of algorithms in computer processing of medical images Contains over 60 pages of stunning, four-color images

Advances in Computational Techniques for Biomedical Image Analysis

Advances in Computational Techniques for Biomedical Image Analysis
Author: Deepika Koundal,Savita Gupta
Publsiher: Academic Press
Total Pages: 322
Release: 2020-05-28
ISBN 10: 0128204117
ISBN 13: 9780128204115
Language: EN, FR, DE, ES & NL

Advances in Computational Techniques for Biomedical Image Analysis Book Review:

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. Covers various challenges and common research issues related to biomedical image analysis Describes advanced computational approaches for biomedical image analysis Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization Explores cloud based medical imaging together with medical imaging security and forensics

Biomedical Image Processing

Biomedical Image Processing
Author: Thomas Martin Deserno
Publsiher: Springer Science & Business Media
Total Pages: 595
Release: 2011-03-01
ISBN 10: 9783642158162
ISBN 13: 3642158161
Language: EN, FR, DE, ES & NL

Biomedical Image Processing Book Review:

In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.

Histopathological Image Analysis in Medical Decision Making

Histopathological Image Analysis in Medical Decision Making
Author: Dey, Nilanjan,Ashour, Amira S.,Kalia, Harihar,Goswami, R.T.,Das, Himansu
Publsiher: IGI Global
Total Pages: 340
Release: 2018-09-21
ISBN 10: 1522563172
ISBN 13: 9781522563174
Language: EN, FR, DE, ES & NL

Histopathological Image Analysis in Medical Decision Making Book Review:

Medical imaging technologies play a significant role in visualization and interpretation methods in medical diagnosis and practice using decision making, pattern classification, diagnosis, and learning. Progressions in the field of medical imaging lead to interdisciplinary discovery in microscopic image processing and computer-assisted diagnosis systems, and aids physicians in the diagnosis and early detection of diseases. Histopathological Image Analysis in Medical Decision Making provides emerging research exploring the theoretical and practical applications of image technologies and feature extraction procedures within the medical field. Featuring coverage on a broad range of topics such as image classification, digital image analysis, and prediction methods, this book is ideally designed for medical professionals, system engineers, medical students, researchers, and medical practitioners seeking current research on problem-oriented processing techniques in imaging technologies.

Computer Vision Approaches to Medical Image Analysis

Computer Vision Approaches to Medical Image Analysis
Author: Reinhard R. Beichel
Publsiher: Springer Science & Business Media
Total Pages: 262
Release: 2006-09-29
ISBN 10: 3540462570
ISBN 13: 9783540462576
Language: EN, FR, DE, ES & NL

Computer Vision Approaches to Medical Image Analysis Book Review:

Medical imaging and medical image analysis are developing rapidly. 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. This was the second time that a satellite workshop,solely devoted to medical image analysis issues, was held in conjunction with the European Conference on Computer Vision (ECCV), and we are optimistic that this will become a tradition at ECCV. We received 38 full-length paper submissions to the second Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, out of which 10 were accepted for oral and 11 for poster presentation after a rigorous peer-review process. In addition, the workshop included three invited talks. The ?rst was given by Maryellen Giger from the University of Chicago, USA — titled “Multi-Modality Breast CADx”.