An Introduction to Deep Learning in Medical Physics: Advantages, Potential, and Challenges

Overview

Journal Phys Med Biol

Publisher IOP Publishing

Specialties Biophysics
Nuclear Medicine
Radiology

Date 2020 Jan 24

PMID 31972556

Citations 44

Authors

Chenyang Shen

Dan Nguyen

Zhiguo Zhou

Steve B Jiang

Bin Dong

Xun Jia

Affiliations

Soon will be listed here.

Abstract

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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