| 期刊全稱 | Artificial Intelligence in Medical Imaging | | 期刊簡(jiǎn)稱 | Opportunities, Appli | | 影響因子2023 | Erik R. Ranschaert,Sergey Morozov,Paul R. Algra | | 視頻video | http://file.papertrans.cn/163/162480/162480.mp4 | | 發(fā)行地址 | Provides a thorough overview of the impact of artificial intelligence (AI) on medical imaging.Includes contributions from radiologists and IT professionals, ensuring a multidisciplinary approach.Makes | | 圖書封面 |  | | 影響因子 | 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 implicationsfor 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 imagi | | Pindex | Book 2019 |
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