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...

Full description

Saved in:
Bibliographic Details
Published in:Physics in medicine & biology Vol. 65; no. 5; p. 05TR01
Main Authors: Shen, Chenyang, Nguyen, Dan, Zhou, Zhiguo, Jiang, Steve B, Dong, Bin, Jia, Xun
Format: Journal Article
Language:English
Published: England 03.03.2020
Subjects:
Deep Learning
Diagnostic Imaging
Humans
Physics
ISSN:1361-6560, 1361-6560
Online Access:Get more information
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:1361-6560
1361-6560
DOI:10.1088/1361-6560/ab6f51