TY - JOUR
T1 - An introduction to deep learning in medical physics
T2 - Advantages, potential, and challenges
AU - Shen, Chenyang
AU - Nguyen, Dan
AU - Zhou, Zhiguo
AU - Jiang, Steve B.
AU - Dong, Bin
AU - Jia, Xun
N1 - Publisher Copyright:
© 2020 Institute of Physics and Engineering in Medicine.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - deep learning
KW - deep neural network
UR - http://www.scopus.com/inward/record.url?scp=85081151192&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081151192&partnerID=8YFLogxK
U2 - 10.1088/1361-6560/ab6f51
DO - 10.1088/1361-6560/ab6f51
M3 - Article
C2 - 31972556
AN - SCOPUS:85081151192
SN - 0031-9155
VL - 65
JO - Physics in medicine and biology
JF - Physics in medicine and biology
IS - 5
M1 - 05TR01
ER -