基于机器学习的放射治疗靶体积自动绘制研究综述

IF 1.3 3区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zhenchao Tao, Shengfei Lyu
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引用次数: 0

摘要

摘要放射治疗是癌症的主要治疗方法之一,放射治疗靶区的划定是精确治疗的基础和前提。以机器学习为代表的人工智能技术在这方面做了大量的研究,提高了目标描绘的准确性和效率。本文将根据医生描绘目标体积的过程,综述机器学习在医学图像匹配、正常器官描绘和治疗目标描绘中的应用和研究,并对其发展前景进行展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Automatic Delineation of Radiotherapy Target Volume based on Machine Learning
ABSTRACT Radiotherapy is one of the main treatment methods for cancer, and the delineation of the radiotherapy target area is the basis and premise of precise treatment. Artificial intelligence technology represented by machine learning has done a lot of research in this area, improving the accuracy and efficiency of target delineation. This article will review the applications and research of machine learning in medical image matching, normal organ delineation and treatment target delineation according to the procudures of doctors to delineate the target volume, and give an outlook on the development prospects.
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来源期刊
Data Intelligence
Data Intelligence COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
6.50
自引率
15.40%
发文量
40
审稿时长
8 weeks
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