[1]方婷,杨一风,贾守强,等.人工智能在急性缺血性脑卒中早期ASPECTS评估中的研究进展[J].中国医学物理学杂志,2023,40(8):1045-1050.[doi:DOI:10.3969/j.issn.1005-202X.2023.08.020]
　FANG Ting,YANG Yifeng,JIA Shouqiang,et al.Artificial intelligence in ASPECTS assessment of acute ischemic stroke: a review[J].Chinese Journal of Medical Physics,2023,40(8):1045-1050.[doi:DOI:10.3969/j.issn.1005-202X.2023.08.020]
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人工智能在急性缺血性脑卒中早期ASPECTS评估中的研究进展()

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
40卷
期数:
2023年第8期
页码:
1045-1050
栏目:
医学人工智能
出版日期:
2023-09-01

文章信息/Info

Title:
Artificial intelligence in ASPECTS assessment of acute ischemic stroke: a review
文章编号:
1005-202X（2023）08-1045-06
作者:
方婷1; 杨一风1; 贾守强2; 聂生东1
1.上海理工大学医学影像工程研究所， 上海 200093； 2.山东第一医科大学附属济南人民医院影像科， 山东 济南 271100
Author(s):
FANG Ting1;  YANG Yifeng1;  JIA Shouqiang2;  NIE Shengdong1
1. Institute of Medical Imaging Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China 2. Department of Imaging, Jinan Peoples Hospital Affiliated to Shandong First Medical University, Jinan 271100, China
关键词:
ASPECTS评分; 急性缺血性脑卒中; 人工智能; 自动化评分; 综述
Keywords:
Keywords: Alberta stroke program early computed tomography score acute ischemic stroke artificial intelligence automatic scoring review
分类号:
R318；R743.3
DOI:
DOI:10.3969/j.issn.1005-202X.2023.08.020
文献标志码:
A
摘要:
急性缺血性脑卒中（AIS）的早期诊断和及时干预对于降低脑卒中的致死致残率具有重要意义。目前，临床上采用阿尔伯塔卒中项目早期计算机断层扫描评分（ASPECTS）来评估AIS的严重程度，但人为评估方法主观性过强且耗时耗力，极易导致漏诊、误诊。因此，近年来涌现了许多基于人工智能算法对AIS进行ASPECTS自动评分的方法研究。本文对此进行综述，以期为进一步研究探索提供参考。首先，简述ASPECTS评分的可靠性；其次，重点介绍目前基于人工智能的脑区提取及脑区评分的方法，证实计算机辅助ASPECTS评分能够有效提高对病情判断的可靠性；最后，总结现有ASPECTS自动评分方法存在的不足，并对其未来的发展趋势进行展望。
Abstract:
Abstract: The early diagnosis and timely intervention of acute ischemic stroke are of great significance to reduce the mortality and disability rate. Alberta stroke program early computed tomography score (ASPECTS) is currently used to assess the severity of acute ischemic stroke in clinic. The human evaluation is subjective and time-consuming, which is easy to lead to missed diagnosis and misdiagnosis. Therefore, many automatic ASPECTS methods based on artificial intelligence algorithms are emerging. The study briefly introduces the reliability of ASPECTS, focuses on the current methods of brain region extraction and brain region scoring based on artificial intelligence for confirming that computer-assisted ASPECTS can effectively improve the reliability of disease judgment, summarizes the existing problems, and discusses the development trends.

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备注/Memo

备注/Memo:
【收稿日期】2023-02-19 【基金项目】国家自然科学基金（81830052）；上海市自然科学基金（20ZR1438300） 【作者简介】方婷，硕士，研究方向：智能医学影像处理与分析，E-mail: ftpenny217@163.com 【通信作者】聂生东，教授，研究方向：智能医学影像处理与分析，E-mail: nsd4647@163.com；贾守强，教授，研究方向：医学影像诊断，E-mail: jshqlw@163.com
更新日期/Last Update: 2023-09-06