Artificial intelligence in radiotherapy:a technological review

作     者：Ke Sheng Ke Sheng

作者机构：Department of Radiation OncologyUniversity of CaliforniaLos AngelesCA 90095USA 

出 版 物：《Frontiers of Medicine》 (医学前沿（英文版）)

年 卷 期：2020年第14卷第4期

页      面：431-449页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 081104[工学-模式识别与智能系统] 08[工学] 1010[医学-医学技术（可授医学、理学学位）] 0835[工学-软件工程] 100215[医学-康复医学与理疗学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

主　　题：artificial intelligence radiation therapy medical imaging treatment planning quality assurance outcome prediction 

摘      要：Radiation therapy(RT)is widely used to treat *** advances in RT have occurred in the past 30 *** advances,such as three-dimensional image guidance,intensity modulation,and robotics,created challenges and opportunities for the next breakthrough,in which artificial intelligence(AI)will possibly play important *** will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others,particularly those with increased complexity because of technological *** improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the ***,AI may provide new functionalities that facilitate satisfactory *** functionalities include superior images for real-time intervention and adaptive and personalized *** may effectively synthesize and analyze big data for such *** review describes the RT workflow and identifies areas,including imaging,treatment planning,quality assurance,and outcome prediction,that benefit from *** review primarily focuses on deep-learning techniques,although conventional machine-learning techniques are also mentioned.