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基于红外热成像技术与BP神经网络的心肌缺血预诊断方法研究

Myocardial Ischemia Pre-Diagnosis Method Based on Infrared Thermal Imaging and BP Neural Network

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摘要

心肌缺血(MI)是诸多心脏疾病的基础性疾病, 可引发多种致命性心脏病, 然而在体检筛查中极难发现, 病人出现症状时往往错过了最佳治疗时间, 因此, 心肌缺血的早期发现和早期干预是控制心脏功能衰减或疾病恶化的关键。采集165位健康和有不同程度心肌缺血患者的红外热图像, 将所有样本集分为训练集和测试集, 通过对红外热图像人体几何定位, 提取心前区左右两侧温差集合, 并使用多种卷积核对温差集合做降维处理, 最终通过反向传播(BP)神经网络在留一法交叉验证下对训练集训练, 并确定网络参数, 建立分类模型。3×3尺寸的高斯核算子对温差集合卷积后, 测试集在BP神经网络上分类准确率达到95.56%, 可以为新样本做出准确预测。该方法能够快捷、准确地辅助临床体检对心肌缺血的早期预警, 为心肌缺血预诊断提供了新的思路。

Abstract

Myocardial ischemia (MI) is a heart disease that can cause various types of fatal heart attacks. Patients often miss the best treatment time when they develop the symptoms of a heart attack. Early detection of MI is considered to be necessary for curbing the deterioration of heart diseases because it is difficult to observe the symptoms of a heart attack through a medical check-up. Infrared thermal images of 165 healthy patients with different degrees of MI are collected, and all the samples are divided into training set and test set. Further, the geometrical differences between the left and right sides of the precordial area are extracted based on the geometric positioning of the infrared thermal image of a particular human body. Additionally, several convolutional kernels are used to reduce the dimensionality of the temperature difference set.The training set is trained using the back-propagation (BP) neural network based on the cross-validation method, and the network parameters are determined for establishing a classification model. After the 3×3 size Gaussian kernel operator is convolved on the temperature difference set, the classification accuracy of the test set with respect to the BP neural network becomes 95.56%, thereby denoting that the predictions for the new sample are considerably accurate. Further, the proposed method can rapidly and accurately assist during the early detection of MI in a clinical examination and provide a new methodology for the pre-diagnosis of MI.

Newport宣传-MKS新实验室计划
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中图分类号:R318.5;O657.3

DOI:10.3788/lop56.011101

所属栏目:成像系统

基金项目:国家自然科学基金(61273019, 61501397, 61201111, 61401080, 61601106)

收稿日期:2018-09-03

修改稿日期:2018-09-21

网络出版日期:2018-09-27

作者单位    点击查看

宓保宏:燕山大学电气工程学院, 河北 秦皇岛 066004
洪文学:燕山大学电气工程学院, 河北 秦皇岛 066004
宋佳霖:燕山大学电气工程学院, 河北 秦皇岛 066004
吴士明:陆军军医大学新桥医院疼痛科, 重庆 400000
孟辉:燕山大学电气工程学院, 河北 秦皇岛 066004

联系人作者:洪文学(hongwx@ysu.edu.cn)

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引用该论文

Mi Baohong,Hong Wenxue,Song Jialin,Wu Shiming,Meng Hui. Myocardial Ischemia Pre-Diagnosis Method Based on Infrared Thermal Imaging and BP Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(1): 011101

宓保宏,洪文学,宋佳霖,吴士明,孟辉. 基于红外热成像技术与BP神经网络的心肌缺血预诊断方法研究[J]. 激光与光电子学进展, 2019, 56(1): 011101

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