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Author: Dr. Nilima Rakesh Dhumale
Publisher: Vinsa Publishing
ISBN: 8196287461
Category : Medical
Languages : en
Pages : 324
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Book Description
Deep learning has become a game-changer in the field of medical diagnosis, completely altering how medical images are analysed and interpreted. This comprehensive book, titled "Deep Learning for Medical Image Analysis" provides a thorough exploration of this rapidly evolving field, guiding readers through the intricacies of deep learning and their applications in medical imaging. Authored by experienced Professors in the field, this book probes into the principles of deep learning, methodically explaining the concepts. The authors effectively bridge the gap between theoretical groundworks and practical uses, representing how deep learning can be harnessed to tackle a wide range of medical image analysis tasks. One of the key strengths of this book lies in its comprehensive coverage of various deep learning-based techniques for medical image analysis. From image segmentation and registration to disease classification and prediction, the book methodically explains the application of deep learning in each domain. The authors provide insightful examples and case studies, showcasing the realworld impact of deep learning in medical diagnosis and treatment planning. The book also delves into the challenges and limitations of deep learning in medical image analysis, addressing issues such as data scarcity, bias, and explainability. The authors encourage critical thinking and discussion, emphasizing the importance of responsible AI development in healthcare. "Deep Learning for Medical Image Analysis" serves as an invaluable resource for researchers, practitioners, and students in the fields of medical imaging, computer vision, and artificial intelligence. Its wide-ranging coverage, clear explanations, and practical examples make it an excellent guide for anyone seeking to understand and apply deep learning techniques in the realm of medical image analysis.
Author: Klaus D. Toennies
Publisher: Springer Science & Business Media
ISBN: 144712751X
Category : Computers
Languages : en
Pages : 477
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Book Description
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.
Author: Snehan Biswas
Publisher: CRC Press
ISBN: 1040172334
Category : Technology & Engineering
Languages : en
Pages : 199
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Book Description
This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.
Author: Isaac Bankman
Publisher: Elsevier
ISBN: 008055914X
Category : Computers
Languages : en
Pages : 1009
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Book Description
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
Author: Paul Suetens
Publisher: Cambridge University Press
ISBN: 1108211208
Category : Medical
Languages : en
Pages : 271
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Book Description
This third edition provides a concise and generously illustrated survey of the complete field of medical imaging and image computing, explaining the mathematical and physical principles and giving the reader a clear understanding of how images are obtained and interpreted. Medical imaging and image computing are rapidly evolving fields, and this edition has been updated with the latest developments in the field, as well as new images and animations. An introductory chapter on digital image processing is followed by chapters on the imaging modalities: radiography, CT, MRI, nuclear medicine and ultrasound. Each chapter covers the basic physics and interaction with tissue, the image reconstruction process, image quality aspects, modern equipment, clinical applications, and biological effects and safety issues. Subsequent chapters review image computing and visualization for diagnosis and treatment. Engineers, physicists and clinicians at all levels will find this new edition an invaluable aid in understanding the principles of imaging and their clinical applications.
Author: David Wilson
Publisher: Springer Science & Business Media
ISBN: 0306485516
Category : Medical
Languages : en
Pages : 661
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Book Description
Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry . Key Features: - Principles of intra-vascular ultrasound (IVUS) - Principles of positron emission tomography (PET) - Physical principles of magnetic resonance angiography (MRA). - Basic and advanced level set methods - Shape for shading method for medical image analysis - Wavelet transforms and other multi-scale analysis functions - Three dimensional deformable surfaces - Level Set application for CT lungs, brain MRI and MRA volume segmentation - Segmentation of incomplete tomographic medical data sets - Subjective level sets for missing boundaries for segmentation
Author: G.R. SINHA
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120349024
Category : Technology & Engineering
Languages : en
Pages : 270
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Book Description
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.
Author: Lena Costaridou
Publisher: CRC Press
ISBN: 0203500458
Category : Medical
Languages : en
Pages : 505
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Book Description
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
Author: Dr. Nilima Rakesh Dhumale
Publisher: Vinsa Publishing
ISBN: 8196287461
Category : Medical
Languages : en
Pages : 324
Get Book Here
Book Description
Deep learning has become a game-changer in the field of medical diagnosis, completely altering how medical images are analysed and interpreted. This comprehensive book, titled "Deep Learning for Medical Image Analysis" provides a thorough exploration of this rapidly evolving field, guiding readers through the intricacies of deep learning and their applications in medical imaging. Authored by experienced Professors in the field, this book probes into the principles of deep learning, methodically explaining the concepts. The authors effectively bridge the gap between theoretical groundworks and practical uses, representing how deep learning can be harnessed to tackle a wide range of medical image analysis tasks. One of the key strengths of this book lies in its comprehensive coverage of various deep learning-based techniques for medical image analysis. From image segmentation and registration to disease classification and prediction, the book methodically explains the application of deep learning in each domain. The authors provide insightful examples and case studies, showcasing the realworld impact of deep learning in medical diagnosis and treatment planning. The book also delves into the challenges and limitations of deep learning in medical image analysis, addressing issues such as data scarcity, bias, and explainability. The authors encourage critical thinking and discussion, emphasizing the importance of responsible AI development in healthcare. "Deep Learning for Medical Image Analysis" serves as an invaluable resource for researchers, practitioners, and students in the fields of medical imaging, computer vision, and artificial intelligence. Its wide-ranging coverage, clear explanations, and practical examples make it an excellent guide for anyone seeking to understand and apply deep learning techniques in the realm of medical image analysis.
Author: Jasjit S. Suri
Publisher: Springer Science & Business Media
ISBN: 9780306486050
Category : Computer vision
Languages : en
Pages : 858
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Book Description
Author: Klaus D. Toennies
Publisher: Springer
ISBN: 1447173201
Category : Computers
Languages : en
Pages : 609
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Book Description
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.
