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Image Processing For Automated Diagnosis Of Cardiac Diseases
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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 240 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
Book Synopsis Cardiovascular Imaging and Image Analysis by : Ayman El-Baz
Download or read book Cardiovascular Imaging and Image Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2018-10-03 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis. It includes several prominent imaging modalities such as MRI, CT, and PET technologies. There is a special emphasis placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. Novel 4D based approach is a unique characteristic of this product. This is a comprehensive multi-contributed reference work that will detail the latest developments in spatial, temporal, and functional cardiac imaging. The main aim of this book is to help advance scientific research within the broad field of early detection of cardiovascular disease. This book focuses on major trends and challenges in this area, and it presents work aimed to identify new techniques and their use in biomedical image analysis. Key Features: Includes state-of-the art 4D cardiac image analysis Explores the aspect of automated segmentation of cardiac CT and MR images utilizing both 3D and 4D techniques Provides a novel procedure for improving full-cardiac strain estimation in 3D image appearance characteristics Includes extensive references at the end of each chapter to enhance further study
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.
Book Synopsis Machine Learning in Cardiovascular Medicine by : Subhi J. Al'Aref
Download or read book Machine Learning in Cardiovascular Medicine written by Subhi J. Al'Aref and published by Academic Press. This book was released on 2020-11-20 with total page 456 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
Book Synopsis Practical Signal and Image Processing in Clinical Cardiology by : Jeffrey J Goldberger
Download or read book Practical Signal and Image Processing in Clinical Cardiology written by Jeffrey J Goldberger and published by Springer Science & Business Media. This book was released on 2010-07-28 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern signal and image acquisition systems used in the field of cardiology acquire, analyze, and store data digitally. Surface electrocardiography, intra-cardiac electrogram recording, echocardiograms, x-ray, magnetic resonance imaging, and computed tomography are among the modalities in the cardiology field where signal processing is applied. Digital signal processing techniques allow us to automate many of the analyses that had previously been done manually with greater precision, accuracy and speed, as well as detect features and patterns in data that may be too subtle to observe by eye. As more cardiologists are becoming more reliant on such technology, a basic understanding of digital signals and the techniques used to extract information from these signals are required.
Book Synopsis Medical Imaging and Health Informatics by : Tushar H. Jaware
Download or read book Medical Imaging and Health Informatics written by Tushar H. Jaware and published by John Wiley & Sons. This book was released on 2022-05-26 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: MEDICAL IMAGING AND HEALTH INFORMATICS Provides a comprehensive review of artificial intelligence (AI) in medical imaging as well as practical recommendations for the usage of machine learning (ML) and deep learning (DL) techniques for clinical applications. Medical imaging and health informatics is a subfield of science and engineering which applies informatics to medicine and includes the study of design, development, and application of computational innovations to improve healthcare. The health domain has a wide range of challenges that can be addressed using computational approaches; therefore, the use of AI and associated technologies is becoming more common in society and healthcare. Currently, deep learning algorithms are a promising option for automated disease detection with high accuracy. Clinical data analysis employing these deep learning algorithms allows physicians to detect diseases earlier and treat patients more efficiently. Since these technologies have the potential to transform many aspects of patient care, disease detection, disease progression and pharmaceutical organization, approaches such as deep learning algorithms, convolutional neural networks, and image processing techniques are explored in this book. This book also delves into a wide range of image segmentation, classification, registration, computer-aided analysis applications, methodologies, algorithms, platforms, and tools; and gives a holistic approach to the application of AI in healthcare through case studies and innovative applications. It also shows how image processing, machine learning and deep learning techniques can be applied for medical diagnostics in several specific health scenarios such as COVID-19, lung cancer, cardiovascular diseases, breast cancer, liver tumor, bone fractures, etc. Also highlighted are the significant issues and concerns regarding the use of AI in healthcare together with other allied areas, such as the Internet of Things (IoT) and medical informatics, to construct a global multidisciplinary forum. Audience The core audience comprises researchers and industry engineers, scientists, radiologists, healthcare professionals, data scientists who work in health informatics, computer vision and medical image analysis.
Book Synopsis Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing by : Rajesh Kumar Tripathy
Download or read book Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing written by Rajesh Kumar Tripathy and published by Elsevier. This book was released on 2024-06-17 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals. In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered. Provides details regarding the application of various signal processing and machine learning-based methods for cardiovascular signal analysis Covers methodologies as well as experimental results and studies Helps readers understand the use of different cardiac signals such as ECG, PCG, and PPG for the automated detection of heart ailments and other related biomedical applications
Book Synopsis Cardiovascular and Coronary Artery Imaging by : Ayman S. El-Baz
Download or read book Cardiovascular and Coronary Artery Imaging written by Ayman S. El-Baz and published by Academic Press. This book was released on 2021-11-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book includes several prominent imaging modalities, such as MRI, CT and PET technologies. A special emphasis is placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. This is a comprehensive, multi-contributed reference work that details the latest developments in spatial, temporal and functional cardiac imaging. Takes an integrated approach to cardiovascular and coronary imaging, covering machine learning, deep learning and reinforcement learning approaches Covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis Provides a perspective on future cardiovascular imaging and highlights areas that still need improvement
Book Synopsis Cardiovascular and Coronary Artery Imaging by : Ayman S. El-Baz
Download or read book Cardiovascular and Coronary Artery Imaging written by Ayman S. El-Baz and published by Academic Press. This book was released on 2022-11-22 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cardiovascular and Coronary Artery Imaging, Volume Two presents the basics of echocardiography, nuclear imaging and magnetic resonance imaging (MRI) and provides insights into their appropriate use. The book covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular and coronary artery disease diagnosis. It includes several prominent imaging modalities such as MRI, CT and PET technologies. Other sections focus on major trends and challenges in this area and present the latest techniques for cardiovascular and coronary image analysis. Takes an integrated approach to cardiovascular and coronary imaging using machine learning, deep learning and reinforcement learning approaches Covers state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis Provides a perspective on future cardiovascular imaging and highlights areas that still need improvement
Book Synopsis Advances in Deep Learning for Medical Image Analysis by : Archana Mire
Download or read book Advances in Deep Learning for Medical Image Analysis written by Archana Mire and published by CRC Press. This book was released on 2022-04-26 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases. The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.
Book Synopsis Deep Learning in Medical Image Analysis by : R. Indrakumari
Download or read book Deep Learning in Medical Image Analysis written by R. Indrakumari and published by CRC Press. This book was released on 2024-07-10 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a reference text and provides a comprehensive overview of conceptual and practical knowledge about deep learning in medical image processing techniques. The post-pandemic situation teaches us the importance of doctors, medical analysis, and diagnosis of diseases in a rapid manner. This book provides a snapshot of the state of current research between deep learning, medical image processing, and health care with special emphasis on saving human life. The chapters cover a range of advanced technologies related to patient health monitoring, predicting diseases from genomic data, detecting artefactual events in vital signs monitoring data, and managing chronic diseases. This book Delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field Presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data Provides an overview of the physics of medical image processing alongside discussing image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction Highlights the new potential applications of machine learning techniques to the solution of important problems in biomedical image applications This book is for students, scholars, and professionals of biomedical technology and healthcare data analytics.
Book Synopsis Multimodal Imaging of the Heart Muscle - Analysis and Visualization to Aided Diagnosis by : Dominika Kruk
Download or read book Multimodal Imaging of the Heart Muscle - Analysis and Visualization to Aided Diagnosis written by Dominika Kruk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The heart plays a vital role in the functioning of the human body. The function of the human heart is pumping blood throughout the body, supplying oxygen and nutrients to the tissues and removing carbon dioxide and other wastes. Cardiovascular diseases are the first cause of death worldwide. Heart diseases are mainly related to a process called atherosclerosis. This process caused harder blood flow through arteries and finally it can stop the blood flow. It can lead to heart attack and stroke. Early and accurate diagnosis of cardiovascular diseases plays an important role in improving the life of population afflicted heart diseases. Medical imaging is widely used in the diagnosis and monitoring of cardiovascular diseases. Medical imaging is a process of collecting information about a place of interest in the body using a predefined characteristic property that is displayed in the form of an image. Imaging techniques allow clinicians and scientist to see inside the body and provide a wealth of information.Recent advances in medical imaging with meaningful contributions from many fields of science, such us medical physic, chemistry, electrical and computer engineering, and computer science have a large impact on diagnostic radiology. The development of engineering and computer science has given the possibility to obtain high-resolution multidimensional images of the place of interest in the body. This kind of images gives a complex information to analyze the structure and function of the organs for computer-aided diagnosis, more accurate diagnosis or to develop or to direct new therapeutic strategies. The aim of this thesis is to develop a new method, which will allow to obtain more complex and accurate information about myocardial disease by using a computer science's and image processing methods.The main objective of this thesis is to develop a complete method allowing Positron Emission Tomography (PET) and Magnetic Resonance Images (MRI) registration of cardiac images. The main difficulties of the PET-MRI registration are the differences between these two modalities. To decrease these differences, the segmentation method were applied to PET and MRI images. Segmentation of the images can help to extract myocardium from the background and focus just on the registration of the myocardium without the impact of the structure around.
Book Synopsis Convolutional Neural Networks for Medical Image Processing Applications by : Saban Ozturk
Download or read book Convolutional Neural Networks for Medical Image Processing Applications written by Saban Ozturk and published by CRC Press. This book was released on 2022-12-23 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.
Book Synopsis Image Processing Techniques for Automated Diagnosis of Wall Motion Abnormality in Echocardiography Sequences by : Vijayalakshmi Ahanathapillai
Download or read book Image Processing Techniques for Automated Diagnosis of Wall Motion Abnormality in Echocardiography Sequences written by Vijayalakshmi Ahanathapillai and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by : Rohit Raja
Download or read book Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing written by Rohit Raja and published by CRC Press. This book was released on 2020-12-22 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field
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
Book Synopsis Intravascular Imaging: Current Applications and Research Developments by : Tsakanikas, Vasilios D.
Download or read book Intravascular Imaging: Current Applications and Research Developments written by Tsakanikas, Vasilios D. and published by IGI Global. This book was released on 2011-10-31 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Limitations of angiography, the traditional invasive method for assessing vascular pathology, have led to an interest in alternative invasive techniques that visualize the arterial wall and allow characterization of plaque type. These alternative techniques, which include intravascular ultrasound, angioscopy, thermography, optical coherence tomography, near infrared spectroscopy, and intravascular magnetic resonance imaging are able to provide valuable information regarding plaque vulnerability, the composition of plaque, and luminal morphology. Intravascular Imaging: Current Applications and Research Developments presents all available intravascular imaging techniques and analyzes their impact in clinical practice and research. This publication aims to inform medical specialists, biomedical engineers, bioinfomaticians, and researchers of current developments and future trends in intravascular imaging techniques, promoting continued evolution of this discipline.
