An introduction to deep learning in medical physics: advantages, potential, and challenges

As one of the most popular approaches in artificial intelligence, deep learning (DL) has attracted a lot of attention in the medical physics field over the past few years. The goals of this topical review article are twofold. First, we will provide an overview of the method to medical physics resear...

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Vydáno v:Physics in medicine & biology Ročník 65; číslo 5; s. 05TR01
Hlavní autoři: Shen, Chenyang, Nguyen, Dan, Zhou, Zhiguo, Jiang, Steve B, Dong, Bin, Jia, Xun
Médium: Journal Article
Jazyk:angličtina
Vydáno: England 03.03.2020
Témata:
Deep Learning
Diagnostic Imaging
Humans
Physics
ISSN:1361-6560, 1361-6560
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Shrnutí:As one of the most popular approaches in artificial intelligence, deep learning (DL) has attracted a lot of attention in the medical physics field over the past few years. The goals of this topical review article are twofold. First, we will provide an overview of the method to medical physics researchers interested in DL to help them start the endeavor. Second, we will give in-depth discussions on the DL technology to make researchers aware of its potential challenges and possible solutions. As such, we divide the article into two major parts. The first part introduces general concepts and principles of DL and summarizes major research resources, such as computational tools and databases. The second part discusses challenges faced by DL, present available methods to mitigate some of these challenges, as well as our recommendations.
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ISSN:1361-6560
1361-6560
DOI:10.1088/1361-6560/ab6f51