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Artificial Intelligence in Medical Imaging Opportunities, Applications and Risks [electronic resource]
Ranschaert, Erik R
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| 자료유형 | 단행본 |
|---|---|
| 개인저자 | Ranschaert, Erik R.,editor. Morozov, Sergey.,editor. Algra, Paul R.,editor. |
| 단체저자명 | SpringerLink (Online service). |
| 서명/저자사항 | Artificial Intelligence in Medical Imaging [electronic resource] : Opportunities, Applications and Risks / edited by Erik R. Ranschaert, Sergey Morozov, Paul R. Algra. |
| 판사항 | 1st ed. 2019. |
| 형태사항 | XV, 373 p. 104 illus., 81 illus. in color:online resource. |
| 기본자료 저록 | Springer Nature eBook |
| 기타형태 저록 | Printed edition:9783319948775Printed edition:9783319948799 |
| ISBN | 9783319948782 |
| 기타표준부호 | 10.1007/978-3-319-94878-2 |
| 내용주기 | PART I: INTRODUCTION: Introduction: Game changers in radiology -- PART II: TECHNIQUES: The role of medical imaging computing, informatics and machine learning in healthcare -- History and evolution of A.I. in medical imaging -- Deep Learning and Neural Networks in imaging: basic principles -- PART III DEVELOPMENT of AI APPLICATIONS: Imaging biomarkers -- How to develop A.I. applications -- Validation of A.I. applications -- PART IV: BIG DATA IN RADIOLOGY: The value of enterprise imaging -- Data mining in radiology -- Image biobanks -- The quest for medical images and data -- Clearance of medical images and data -- Legal and ethical issues in AI -- PART V: CLINICAL USE OF A.I. IN RADIOLOGY: Pulmonary diseases -- Cardiac diseases -- Breast cancer -- Neurological diseases -- PART VI: IMPACT of A.I. on RADIOLOGY: Applications of A.I. beyond image analysis -- Value of structured reporting for A.I. -- The role of A.I. for clinical trials -- Market and economy of A.I.: evolution -- The role of an A.I. ecosystem for radiology -- Advantages and risks of A.I. for radiologists -- Re-thinking radiology. |
| 요약 | 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. |
| 일반주제명 | Radiology. Computer networks . Medical informatics. Radiology. Computer Communication Networks. Health Informatics. |
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