Image Processing For Automated Diagnosis Of Cardiac Diseases

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Image Processing for Automated Diagnosis of Cardiac Diseases

Author : Kalpana Chauhan
Publisher : Academic Press
ISBN 13 : 0323850650
Total Pages : 242 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Image Processing for Automated Diagnosis of Cardiac Diseases by : Kalpana Chauhan

Download or read book Image Processing for Automated Diagnosis of Cardiac Diseases written by Kalpana Chauhan and published by Academic Press. This book was released on 2021-07-13 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease. - Includes advanced techniques to improve diagnostic methods for various cardiac diseases - Uses methods to improve the existing diagnostic features of echocardiographic machines - Develops new diagnostic features for echocardiographic machines

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. - 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

Machine Learning in Cardiovascular Medicine

Author : Subhi J. Al'Aref, M.D.
Publisher : Academic Press
ISBN 13 : 0128202734
Total Pages : 454 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Machine Learning in Cardiovascular Medicine by : Subhi J. Al'Aref, M.D.

Download or read book Machine Learning in Cardiovascular Medicine written by Subhi J. Al'Aref, M.D. and published by Academic Press. This book was released on 2020-12-11 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert
Publisher : Springer
ISBN 13 : 3319948784
Total Pages : 369 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Sources of Medical Technology

Author : Committee on Technological Innovation in Medicine
Publisher : National Academies Press
ISBN 13 : 0309587611
Total Pages : 255 pages
Book Rating : 4.3/5 (95 download)

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Book Synopsis Sources of Medical Technology by : Committee on Technological Innovation in Medicine

Download or read book Sources of Medical Technology written by Committee on Technological Innovation in Medicine and published by National Academies Press. This book was released on 1995-01-15 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence suggests that medical innovation is becoming increasingly dependent on interdisciplinary research and on the crossing of institutional boundaries. This volume focuses on the conditions governing the supply of new medical technologies and suggest that the boundaries between disciplines, institutions, and the private and public sectors have been redrawn and reshaped. Individual essays explore the nature, organization, and management of interdisciplinary R&D in medicine; the introduction into clinical practice of the laser, endoscopic innovations, cochlear implantation, cardiovascular imaging technologies, and synthetic insulin; the division of innovating labor in biotechnology; the government- industry-university interface; perspectives on industrial R&D management; and the growing intertwining of the public and proprietary in medical technology.

Research Awards Index

Author :
Publisher :
ISBN 13 :
Total Pages : 776 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Research Awards Index by :

Download or read book Research Awards Index written by and published by . This book was released on 1989 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fundamentals and Methods of Machine and Deep Learning

Author : Pradeep Singh
Publisher : John Wiley & Sons
ISBN 13 : 1119821886
Total Pages : 480 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Fundamentals and Methods of Machine and Deep Learning by : Pradeep Singh

Download or read book Fundamentals and Methods of Machine and Deep Learning written by Pradeep Singh and published by John Wiley & Sons. This book was released on 2022-02-01 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.

Practical Machine Learning and Image Processing

Author : Himanshu Singh
Publisher : Apress
ISBN 13 : 1484241495
Total Pages : 177 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Practical Machine Learning and Image Processing by : Himanshu Singh

Download or read book Practical Machine Learning and Image Processing written by Himanshu Singh and published by Apress. This book was released on 2019-02-26 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will LearnDiscover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.

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.

Intelligent Computing

Author : Kohei Arai
Publisher : Springer Nature
ISBN 13 : 3031622693
Total Pages : 699 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Intelligent Computing by : Kohei Arai

Download or read book Intelligent Computing written by Kohei Arai and published by Springer Nature. This book was released on with total page 699 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Biomedical Image Processing

Author : Thomas Martin Deserno
Publisher : Springer Science & Business Media
ISBN 13 : 3642158161
Total Pages : 617 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Biomedical Image Processing by : Thomas Martin Deserno

Download or read book Biomedical Image Processing written by Thomas Martin Deserno and published by Springer Science & Business Media. This book was released on 2011-03-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Biomedical Data Mining for Information Retrieval

Author : Sujata Dash
Publisher : John Wiley & Sons
ISBN 13 : 111971124X
Total Pages : 450 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Biomedical Data Mining for Information Retrieval by : Sujata Dash

Download or read book Biomedical Data Mining for Information Retrieval written by Sujata Dash and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Artificial Intelligence in Ophthalmology

Author : Andrzej Grzybowski
Publisher : Springer Nature
ISBN 13 : 3030786013
Total Pages : 280 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Artificial Intelligence in Ophthalmology by : Andrzej Grzybowski

Download or read book Artificial Intelligence in Ophthalmology written by Andrzej Grzybowski and published by Springer Nature. This book was released on 2021-10-13 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.

Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

Author : Mihaela Pop
Publisher : Springer
ISBN 13 : 3319755412
Total Pages : 267 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges by : Mihaela Pop

Download or read book Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges written by Mihaela Pop and published by Springer. This book was released on 2018-03-14 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 8th International Workshop on Statistical Atlases and Computational Models of the Heart: ACDC and MMWHS Challenges 2017, held in conjunction with MICCAI 2017, in Quebec, Canada, in September 2017. The 27 revised full workshop papers were carefully reviewed and selected from 35 submissions. The papers cover a wide range of topics computational imaging and modelling of the heart, as well as statistical cardiac atlases. The topics of the workshop included: cardiac imaging and image processing, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods. Besides regular contributing papers, additional efforts of STACOM workshop were also focused on two challenges: ACDC and MM-WHS.

Current and Future Role of Artificial Intelligence in Cardiac Imaging

Author : Steffen Erhard Petersen
Publisher : Frontiers Media SA
ISBN 13 : 2889660583
Total Pages : 138 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Current and Future Role of Artificial Intelligence in Cardiac Imaging by : Steffen Erhard Petersen

Download or read book Current and Future Role of Artificial Intelligence in Cardiac Imaging written by Steffen Erhard Petersen and published by Frontiers Media SA. This book was released on 2020-10-09 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Cardiovascular Computed Tomography

Author : James Stirrup
Publisher :
ISBN 13 : 0198809271
Total Pages : 577 pages
Book Rating : 4.1/5 (988 download)

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Book Synopsis Cardiovascular Computed Tomography by : James Stirrup

Download or read book Cardiovascular Computed Tomography written by James Stirrup and published by . This book was released on 2020 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to performing and analysing cardiovascular scans, this handbook is fully updated in this second edition. Containing a wealth of example scan images and detailed guidance on techniques and interpretations, this book is an invaluable workstation resource.

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 2023-11-23 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