Moritz Rabe, Christopher Kurz, Adrian Thummerer, Guillaume Landry
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引用次数: 0
Abstract
Radiation therapy (RT) is a highly digitized field relying heavily on computational methods and, as such, has a high affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is concerned and is especially so during image-guided RT (IGRT). With the advent of online adaptive RT (ART) workflows at magnetic resonance (MR) linear accelerators (linacs) and at cone-beam computed tomography (CBCT) linacs, the need for automation is further increased. AI as applied to modern IGRT is thus one area of RT where we can expect important developments in the near future. In this review article, after outlining modern IGRT and online ART workflows, we cover the role of AI in CBCT and MRI correction for dose calculation, auto-segmentation on IGRT imaging, motion management, and response assessment based on in-room imaging.
期刊介绍：
Strahlentherapie und Onkologie, published monthly, is a scientific journal that covers all aspects of oncology with focus on radiooncology, radiation biology and radiation physics. The articles are not only of interest to radiooncologists but to all physicians interested in oncology, to radiation biologists and radiation physicists. The journal publishes original articles, review articles and case studies that are peer-reviewed. It includes scientific short communications as well as a literature review with annotated articles that inform the reader on new developments in the various disciplines concerned and hence allow for a sound overview on the latest results in radiooncology research.
Founded in 1912, Strahlentherapie und Onkologie is the oldest oncological journal in the world. Today, contributions are published in English and German. All articles have English summaries and legends. The journal is the official publication of several scientific radiooncological societies and publishes the relevant communications of these societies.
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