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This new edition is a comprehensive source of imaging informatics fundamentals and how those fundamentals are applied in everyday practice. Imaging Informatics Professionals (IIPs) play a critical role in healthcare, and the scope of the profession has grown far beyond the boundaries of the PACS. A successful IIP must understand the PACS itself and all the software systems networked together in the medical environment. Additionally, an IIP must know the workflows of all the imaging team members, have a base in several medical specialties and be fully capable in the realm of information technology. Practical Imaging Informatics has been reorganized to follow a logical progression from basic background information on IT and clinical image management, through daily operations and troubleshooting, to long-term planning. The book has been fully updated to include the latest technologies and procedures, including artificial intelligence and machine learning. Written by a team of renowned international authors from the Society for Imaging Informatics in Medicine and the European Society of Medical Imaging Informatics, this book is an indispensable reference for the practicing IIP. In addition, it is an ideal guide for those studying for a certification exam, biomedical informaticians, trainees with an interest in informatics, and any professional who needs quick access to the nuts and bolts of imaging informatics.
This book provides a unique introduction to the vast field of Medical Imaging Informatics for students and physicians by depicting the basics of the different areas in Radiology Informatics. It features short chapters on the different main areas in Medical Imaging Informatics, such as Picture Archiving and Communication Systems (PACS), radiology reporting, data sharing, and de-identification and anonymization, as well as standards like Digital Imaging and Communications in Medicine (DICOM), Integrating the Health Enterprise (IHE) and Health Level 7 (HL7,. Written by experts in the respective fields and endorsed by the European Society of Medical Imaging Informatics (EuSoMII) the scope of the book is based on the Medical Imaging Informatics sub-sections of the European Society of Radiology (ESR) European Training Curriculum Undergraduate Level and Level I. This volume will be an invaluable resource for residents and radiologists and is also specifically suited for undergraduate training.
Informatics in Medical Imaging provides a comprehensive survey of the field of medical imaging informatics. In addition to radiology, it also addresses other specialties such as pathology, cardiology, dermatology, and surgery, which have adopted the use of digital images. The book discusses basic imaging informatics protocols, picture archiving and communication systems, and the electronic medical record. It details key instrumentation and data mining technologies used in medical imaging informatics as well as practical operational issues, such as procurement, maintenance, teleradiology, and ethics. Highlights Introduces the basic ideas of imaging informatics, the terms used, and how data are represented and transmitted Emphasizes the fundamental communication paradigms: HL7, DICOM, and IHE Describes information systems that are typically used within imaging departments: orders and result systems, acquisition systems, reporting systems, archives, and information-display systems Outlines the principal components of modern computing, networks, and storage systems Covers the technology and principles of display and acquisition detectors, and rounds out with a discussion of other key computer technologies Discusses procurement and maintenance issues; ethics and its relationship to government initiatives like HIPAA; and constructs beyond radiology The technologies of medical imaging and radiation therapy are so complex and computer-driven that it is difficult for physicians and technologists responsible for their clinical use to know exactly what is happening at the point of care. Medical physicists are best equipped to understand the technologies and their applications, and these individuals are assuming greater responsibilities in the clinical arena to ensure that intended care is delivered in a safe and effective manner. Built on a foundation of classic and cutting-edge research, Informatics in Medical Imaging supports and updates medical physicists functioning at the intersection of radiology and radiation.
Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications. Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.
This book provides practitioners and scientists with insights into diverse aspects of structured reporting to allow them to develop tools and a knowledge base to ensure that this electronic reporting trend is widely applied. After an introduction to reporting in radiology, various parts of structured reporting are discussed in detail, including an overview of standardized reporting systems, standardized reporting language, DICOM structured reporting, template based structured reporting, and modular reporting. The last chapter addresses the interaction of structured reporting with artificial intelligence and its impact on the future of radiology. The last chapter addresses the interaction of structured reporting with artificial intelligence and its impact on the future of radiology. Endorsed by the European Society of Medical Imaging Informatics (EuSoMII), the scope of the book is based on the Medical Imaging Informatics sub-sections of the European Society of Radiology (ESR) European Training Curriculum Level I and II. It is a valuable resource for residents, radiologists and students.
Attention SIIM Members: a special discount is available to you; please log in to the SIIM website at www.siim.org/pii or call the SIIM office at 703-723-0432 for information on how you can receive the SIIM member price. Imaging Informatics Professionals (IIPs) have come to play an indispensable role in modern medicine, and the scope of this profession has grown far beyond the boundaries of the PACS. A successful IIP must not only understand the PACS itself, but also have knowledge of clinical workflow, a base in several medical specialties, and a solid IT capability regarding software interactions and networking. With the introduction of a certification test for the IIP position, a single source was needed to explain the fundamentals of imaging informatics and to demonstrate how those fundamentals are applied in everyday practice. Practical Imaging Informatics describes the foundations of information technology and clinical image management, details typical daily operations, and discusses rarer complications and issues.
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.
This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.
Introduction to Clinical Informatics fills a void in the Computer in Health Care series. With this volume, Patrice Degoulet and Marius Fieschi provide a comprehensive view of medical informatics and carry that concept forward into the realm of clinical informatics. The authors draw upon their experi ences as medical school faculty members in France, where informatics has long been integrated into the curriculum and where the French version of this very book has been used, tested, and revised. In intent and content, this volume stands as the companion volume to Introduction to Nursing Informatics, one of the series' best selling titles. For practitioners and students of medicine, pharmacy, and other health profes sions, Introduction to Clinical Informatics offers an essential understanding how computing can support patient care, clarifying practical uses and critical issues. Today medical schools in the United States are making informatics a part of their curriculum, with required medical informatics blocks at the onset of training serving as the base for problem-based learning throughout the course of study. In an increasingly networked and computerized environ ment, health-care providers are having to alter how they practice. Whether in the office, the clinic, or the hospital, health-care professionals have access to a growing array of capabilities and tools as they deliver care. Learning to use these becomes a top priority, and this volume becomes a valuable resource.
This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development