[1]刘雪冰,高永彬.良性阵发性位置性眩晕的辅助诊断[J].中国医学物理学杂志,2023,40(11):1446-1552.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.021]
　LIU Xuebing,GAO Yongbin,et al.Auxiliary diagnosis of benign paroxysmal positional vertigo[J].Chinese Journal of Medical Physics,2023,40(11):1446-1552.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.021]
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良性阵发性位置性眩晕的辅助诊断()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
40卷
期数:
2023年第11期
页码:
1446-1552
栏目:
医学人工智能
出版日期:
2023-11-24

文章信息/Info

Title:
Auxiliary diagnosis of benign paroxysmal positional vertigo
文章编号:
1005-202X（2023）11-1446-07
作者:
刘雪冰1; 2; 高永彬1; 2
1. 上海工程技术大学电子电气工程学院， 上海 201600； 2.上海工程技术大学 智慧医疗研究所， 上海 201600
Author(s):
LIU Xuebing1;  2;  GAO Yongbin1;  2
1. School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201600, China 2. Smart Medical Research Institute, Shanghai University of Engineering Science, Shanghai 201600, China
关键词:
良性阵发性位置性眩晕; 二值化; 阈值化; 模板匹配
Keywords:
Keywords: benign paroxysmal positional vertigo binaryzation thresholding template matching
分类号:
R318；R741
DOI:
DOI:10.3969/j.issn.1005-202X.2023.11.021
文献标志码:
A
摘要:
目的：设计一种利用视觉虹膜识别概念和神经网络来诊断良性阵发性位置性眩晕（BPPV）的方法，从而辅助医生进行诊断。方法：通过计算机视觉二值化和阈值化技术从BPPV患者眼球运动视频中定位瞳孔和虹膜，捕获眼球运动轨迹。在眼球运动过程中使用虹膜模板匹配方法提取瞳孔和眼球运动的特征信息。将获得的眼动数据输入设计的神经网络进行BPPV诊断。结果：通过计算机视觉技术的实时检测和网络学习特征的能力，能有效捕捉并描述眼球运转轨迹，输出当前眼动轨迹信息，辅助医生做出更准确、更迅速的决策。结论：使用这种相对简单、无创且精确的方法来测量扭转眼球运动解决了长期存在的阻碍视觉和眼球运动的问题，能广泛应用于基础和临床研究或诊断测试。
Abstract:
Abstract: Objective To diagnose benign paroxysmal positional vertigo (BPPV) using visual iris recognition concept and neural network for assisting doctors in diagnosis. Methods The pupil and iris were located from the eye movement video of BPPV patients using computer vision binarization and thresholding techniques to capture the eye movement trajectory. During eye movement, iris template matching method was used to extract the feature information of the pupil and eye movement. The obtained data was input into the designed neural network for BPPV diagnosis. Results Through the real-time detection of computer vision technology and the feature learning of network, the proposed method effectively captured and described the eye movement trajectory, and output the eye movement trajectory, thereby assisting doctors in more accurate and faster decision-making. Conclusion Using the proposed method which is relatively simple, non-invasive and accurate to measure torsional eye movements solves the long-standing problems that hinder vision and eye movement, and it can be widely used in basic and clinical researches or diagnostic testing.

相似文献/References:

[1]刘玉红,王志芳,杨佳仪,等.彩色图像二值化算法及应用[J].中国医学物理学杂志,2013,30(01):3873.[doi:10.3969/j.issn.1005-202X.2013.01.009]
[2]贺斌,高永彬.基于非局部卷积和卷积注意力模块的眩晕眼震诊断方法[J].中国医学物理学杂志,2024,41(5):571.[doi:DOI:10.3969/j.issn.1005-202X.2024.05.007]
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备注/Memo

备注/Memo:
【收稿日期】2023-07-06 【基金项目】上海市科委科技创新行动计划社会发展科技攻关项目 （21DZ1204900） 【作者简介】刘雪冰，硕士研究生，研究方向：计算机视觉、医学图像处理，E-mail: L983412889@gmail.com 【通信作者】高永彬，博士，副教授，研究方向：计算机视觉、医学图像处理、深度学习，E-mail: gaoyongbin@sues.edu.cn
更新日期/Last Update: 2023-11-24