期刊
JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES
卷 6, 期 3, 页码 946-957出版社
DOKUZ EYLUL UNIV INST HEALTH SCIENCES
DOI: 10.30621/jbachs.960154
关键词
deep learning; machine learning; radiology; radiation oncology; medical physics
This paper presents the application and development of machine learning and deep learning techniques in the fields of medical physics, radiology, and radiation oncology, and discusses the potential challenges and solutions.
Machine learning (ML) and deep learning (DL) techniques introduced within the fields of medical physics, radiology, and radiation oncology (RO) have come a long way in the past few years. A great many applications have proven to be an efficacious automated diagnosis and radiotherapy system. This paper outlines DL's general concepts and principles, key computational methods, and resources, as well as the implementation of automated models in radiology and RO research. In addition, the potential challenges and solutions of DL technology are also discussed.
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