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Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Author : Patrick Veit-Haibach

Publisher :

Page : 0 pages

File Size : 27,29 MB

Release : 2022

Category :

ISBN : 9783031030956

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Book Description

This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.



Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert

Publisher : Springer

Page : 369 pages

File Size : 23,12 MB

Release : 2019-01-29

Category : Medical

ISBN : 3319948784

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Book Description

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.



Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Author : Patrick Veit-Haibach

Publisher : Springer Nature

Page : 217 pages

File Size : 20,48 MB

Release : 2022-06-22

Category : Medical

ISBN : 3031001192

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Book Description

This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.



Medical Imaging Informatics

Author : Alex A.T. Bui

Publisher : Springer Science & Business Media

Page : 454 pages

File Size : 14,91 MB

Release : 2009-12-01

Category : Technology & Engineering

ISBN : 1441903852

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Book Description

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.



Imaging in Nuclear Medicine

Author : Augusto Giussani

Publisher : Springer Science & Business Media

Page : 236 pages

File Size : 37,71 MB

Release : 2013-03-15

Category : Medical

ISBN : 3642314155

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Book Description

This volume addresses a wide range of issues in the field of nuclear medicine imaging, with an emphasis on the latest research findings. Initial chapters set the scene by considering the role of imaging in nuclear medicine from the medical perspective and discussing the implications of novel agents and applications for imaging. The physics at the basis of the most modern imaging systems is described, and the reader is introduced to the latest advances in image reconstruction and noise correction. Various novel concepts are then discussed, including those developed within the framework of the EURATOM FP7 MADEIRA research project on the optimization of imaging procedures in order to permit a reduction in the radiation dose to healthy tissues. Advances in quality control and quality assurance are covered, and the book concludes by listing rules of thumb for imaging that will be of use to both beginners and experienced researchers.



Medical Imaging

Author : K.C. Santosh

Publisher : CRC Press

Page : 251 pages

File Size : 45,83 MB

Release : 2019-08-20

Category : Computers

ISBN : 0429642490

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Book Description

Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.



Artificial Intelligence in Medical Imaging

Author : Lia Morra

Publisher : CRC Press

Page : 165 pages

File Size : 47,94 MB

Release : 2019-11-25

Category : Science

ISBN : 1000753085

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Book Description

Choice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective



Nuclear Medicine in Oncology

Author : Gang Huang

Publisher : Springer

Page : 346 pages

File Size : 22,49 MB

Release : 2019-06-11

Category : Medical

ISBN : 9811374589

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Book Description

This book introduces molecular imaging and Target Therapy in various cancers. The first part is the subjects and primary focused on the basics of nuclear physics, radiation dosimetry, nuclear medicine equipment and small animal imaging equipment. The second part is about the radiopharmaceutical and commonly used clinical radiopharmaceuticals, including positron emission imaging agent, single photon emission imaging agent, and radionuclide therapy agents as well as their radioactive preparation, quality control, and a brief clinical application were included. Also, this part introduces a number of new imaging agents which were potential value of clinical applications. In the third part, the clinical application of the conventional imaging agent 18F-FDG in different tumors and neurodegenerative diseases and 18F-Dopa imaging in the nervous system are discussed. Besides the clinical applications of 99mTc labeled radiopharmaceuticals in parathyroid disease, coronary heart disease, myocardial infarction, sentinel lymph node, metastatic bone tumors, liver and gallbladder disease in children are introduced. Finally, the applications of radionuclide 131I on treatments of Graves' disease and differentiated thyroid cancer and metastases are investigated respectively. This book is a useful reference for professionals engaged in nuclear medicine and clinical research, including clinical nuclear medicine physicians, nuclear medicine engineers and nuclear medicine pharmacists.



Deep Learning in Medical Image Analysis

Author : Gobert Lee

Publisher : Springer Nature

Page : 184 pages

File Size : 45,25 MB

Release : 2020-02-06

Category : Medical

ISBN : 3030331288

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Book Description

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.



Artificial Intelligence in Cardiothoracic Imaging

Author : Carlo N. De Cecco

Publisher : Springer Nature

Page : 582 pages

File Size : 20,72 MB

Release : 2022-04-22

Category : Medical

ISBN : 3030920879

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Book Description

This book provides an overview of current and potential applications of artificial intelligence (AI) for cardiothoracic imaging. Most AI systems used in medical imaging are data-driven and based on supervised machine learning. Clinicians and AI specialists can contribute to the development of an AI system in different ways, focusing on their respective strengths. Unfortunately, communication between these two sides is far from fluent and, from time to time, they speak completely different languages. Mutual understanding and collaboration are imperative because the medical system is based on physicians’ ability to take well-informed decisions and convey their reasoning to colleagues and patients. This book offers unique insights and informative chapters on the use of AI for cardiothoracic imaging from both the technical and clinical perspective. It is also a single comprehensive source that provides a complete overview of the entire process of the development and use of AI in clinical practice for cardiothoracic imaging. The book contains chapters focused on cardiac and thoracic applications as well more general topics on the potentials and pitfalls of AI in medical imaging. Separate chapters will discuss the valorization, regulations surrounding AI, cost-effectiveness, and future perspective for different countries and continents. This book is an ideal guide for clinicians (radiologists, cardiologists etc.) interested in working with AI, whether in a research setting developing new AI applications or in a clinical setting using AI algorithms in clinical practice. The book also provides clinical insights and overviews for AI specialists who want to develop clinically relevant AI applications.