Artificial Intelligence in Medical Imaging PDF Download
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Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
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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.
Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
Get Book Here
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.
Author: Sharma, Avinash Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 327
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Book Description
Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes. Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.
Author: Lia Morra
Publisher: CRC Press
ISBN: 1000753085
Category : Science
Languages : en
Pages : 165
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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
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Author: K.C. Santosh
Publisher: CRC Press
ISBN: 0429642490
Category : Computers
Languages : en
Pages : 251
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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.
Author: Alex A.T. Bui
Publisher: Springer Science & Business Media
ISBN: 1441903852
Category : Technology & Engineering
Languages : en
Pages : 454
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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.
Author: Saxena, Sanjay
Publisher: IGI Global
ISBN: 1799850722
Category : Medical
Languages : en
Pages : 274
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Book Description
Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.
Author: Steffen Erhard Petersen
Publisher: Frontiers Media SA
ISBN: 2889660583
Category : Medical
Languages : en
Pages : 138
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Book Description
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.
Author: Surbhi Bhatia
Publisher: Springer Nature
ISBN: 3030670511
Category : Technology & Engineering
Languages : en
Pages : 323
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Book Description
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
Author: Hani H. Abujudeh
Publisher: Oxford University Press
ISBN: 0199938237
Category : Medical
Languages : en
Pages : 373
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Book Description
Radiology has been transformed by new imaging advances and a greater demand for imaging, along with a much lower tolerance for error as part of the Quality & Safety revolution in healthcare. With a greater emphasis on patient safety and quality in imaging practice, imaging specialists are increasingly charged with ensuring patient safety and demonstrating that everything done for patients in their care meets the highest quality and safety standards. This book offers practical guidance on understanding, creating, and implementing quality management programs in Radiology. Chapters are comprehensive, detailed, and organized into three sections: Core Concepts, Management Concepts, and Educational & Special Concepts. Discussions are applicable to all practice settings: community hospitals, private practice, academic radiology, and government/military practice, as well as to those preparing for the quality and safety questions on the American Board of Radiology's "Maintenance of Certification" or initial Board Certification Examinations. Bringing together the various elements that comprise the quality and safety agenda for Radiology, this book serves as a thorough roadmap and resource for radiologists, technicians, and radiology managers and administrators.
