[1]莫梓华,高红霞,黄飚.人工智能在中枢神经系统疾病影像诊断中的应用进展[J].中国医学物理学杂志,2020,37(6):792-796.[doi:DOI:10.3969/j.issn.1005-202X.2020.06.025]
　MO Zihua,GAO Hongxia,et al.Application of artificial intelligence in imaging diagnosis of central nervous system diseases: a review[J].Chinese Journal of Medical Physics,2020,37(6):792-796.[doi:DOI:10.3969/j.issn.1005-202X.2020.06.025]
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人工智能在中枢神经系统疾病影像诊断中的应用进展()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第6期
页码:
792-796
栏目:
医学人工智能
出版日期:
2020-06-25

文章信息/Info

Title:
Application of artificial intelligence in imaging diagnosis of central nervous system diseases: a review
文章编号:
1005-202X（2020）06-0792-05
作者:
莫梓华1; 2; 高红霞1; 黄飚2
1.华南理工大学自动化科学与工程学院， 广东 广州 510641； 2.华南理工大学附属广东省人民医院放射科， 广东 广州 510080
Author(s):
MO Zihua1;  2;  GAO Hongxia1;  HUANG Biao2
1. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China 2. Department of Radiology, Guangdong Provincial Peoples Hospital, South China University of Technology, Guangzhou 510080, china
关键词:
人工智能; 中枢神经系统疾病; 影像诊断; 综述
Keywords:
Keywords: artificial intelligence central nervous system disease imaging diagnosis review
分类号:
R319
DOI:
DOI:10.3969/j.issn.1005-202X.2020.06.025
文献标志码:
A
摘要:
人工智能（AI）技术应用于中枢神经系统疾病的诊断、分型以及预后，可显著提高医学影像信息的可信性和有效性，大幅提高神经系统疾病早期诊断的准确率，为医生选择合理的治疗方案提供定量的依据。本研究介绍了AI在中枢神经影像诊断中常用的学习算法、AI在中枢神经疾病影像诊断中的图像分割和特征提取中的应用；综述了AI在术前胶质瘤分级、预测基因突变状况以及胶质瘤术后复发鉴别的应用；并初步介绍了已用于临床工作的一些软件工具。
Abstract:
Abstract: The application of artificial intelligence (AI) technology in the diagnosis, classification and prognosis of central nervous system diseases can significantly improve the credibility and validity of medical imaging information, greatly improve the accuracy of early diagnosis of neurological diseases and provide quantitative data for doctors to choose the optimal treatment program. Herein the widely-used learning algorithms of AI and the applications of AI in image segmentation and feature extraction during the imaging diagnosis of central nervous system diseases are introduced. Meanwhile, the applications of AI in the preoperative classification of glioma, the preoperative prediction of gene mutation, and the identification of postoperative recurrence in patients with glioma are summarized. Finally, some of the software tools that have been used in clinic are introduced briefly.

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备注/Memo

备注/Memo:
【收稿日期】2020-01-10 【基金项目】广东省重点领域研发计划（2018B030339001） 【作者简介】莫梓华，在读研究生，研究方向：医学图像处理，E-mail: 577900893@qq.com 【通信作者】黄飚，教授，研究方向：神经系统疾病诊断，E-mail: syhuangbiao@scut.edu.cn
更新日期/Last Update: 2020-07-03