Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

Acharya U. Rajendra; Fujita Hamido; Lih Oh Shu; Adam Muhammad; Tan Jen Hong; Chua Chua Kuang

首页> 外文期刊>Knowledge-Based Systems >Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

【24h】

Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

机译：通过卷积神经网络使用不同持续时间的心电图节段自动检测冠状动脉疾病

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Coronary artery disease (CAD) is caused due by the blockage of inner walls of coronary arteries by plaque. This constriction reduces the blood flow to the heart muscles resulting in myocardial infarction (MI). The electrocardiogram (ECG) is commonly used to screen the cardiac health. The ECG signals are nonstationary and nonlinear in nature whereby the transient disease indicators may appear randomly on the time scale. Therefore, the procedure to diagnose the abnormal beat is arduous, time consuming and prone to human errors. The automated diagnosis system overcomes these problems. In this study, convolutional neural network (CNN) structures comprising of four convolutional layers, four max pooling layers and three fully connected layers are proposed for the diagnosis of CAD using two and five seconds durations of ECG signal segments. Deep CNN is able to differentiate between normal and abnormal ECG with an accuracy of 94.95%, sensitivity of 93.72%, and specificity of 95.18% for Net 1 (two seconds) and accuracy of 95.11%, sensitivity of 91.13% and specificity of 95.88% for Net 2 (5 s). The proposed system can help the clinicians in their accurate and reliable decision making of CAD using ECG signals. (C) 2017 Elsevier B.V. All rights reserved.

机译：冠状动脉疾病（CAD）是由斑块阻塞冠状动脉内壁引起的。这种收缩会减少流向心肌的血液，从而导致心肌梗塞（MI）。心电图（ECG）通常用于筛查心脏健康状况。 ECG信号本质上是非平稳的和非线性的，因此瞬时疾病指标可能会在时间范围内随机出现。因此，诊断异常搏动的过程繁琐，耗时且容易发生人为错误。自动化诊断系统克服了这些问题。在这项研究中，提出了由四个卷积层，四个最大池化层和三个完全连接层组成的卷积神经网络（CNN）结构，用于使用两秒和五秒的ECG信号段持续时间诊断CAD。 Deep CNN能够区分正常和异常心电图，其准确度为94.95％，灵敏度为93.72％，对Net 1（两秒）的特异性为95.18％，准确度为95.11％，灵敏度为91.13％，特异性为95.88％净2（5 s）。所提出的系统可以帮助临床医生使用ECG信号做出准确，可靠的CAD决策。（C）2017 Elsevier B.V.保留所有权利。

著录项

来源
《Knowledge-Based Systems》 |2017年第15期|62-71|共10页
作者
Acharya U. Rajendra; Fujita Hamido; Lih Oh Shu; Adam Muhammad; Tan Jen Hong; Chua Chua Kuang;
展开▼
作者单位

Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore, Singapore|SUSS Univ, Sch Sci & Technol, Dept Biomed Engn, Singapore, Singapore|Univ Malaya, Fac Engn, Dept Biomed Engn, Kuala Lumpur, Malaysia;

Iwate Prefectural Univ, Fac Software & Informat Sci, Takizawa, Iwate 0200693, Japan;

Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore, Singapore;

Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore, Singapore;

Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore, Singapore;

Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore, Singapore;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
CAD; ECG; CNN; Feature; Heart; Training; Testing;

机译：CAD;ECG;CNN;功能;心脏;培训;测试;

相似文献

外文文献
中文文献
专利

1. Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network [J] . Acharya U. Rajendra, Fujita Hamido, Lih Oh Shu, Information Sciences: An International Journal . 2017,第期

机译：使用卷积神经网络的不同间隔的不同间隔自动检测心律失常的心律失常
2. Arrhythmia detection using deep convolutional neural network with long duration ECG signals [J] . Yildirim Ozal, Plawiak Pawel, Tan Ru-San, Computers in Biology and Medicine . 2018,第期

机译：使用长期ECG信号使用深卷积神经网络的心律失常检测
3. Automated detection of atrial Fibrillation and atrial flutter in ECG signals based on convolutional and improved Elman neural network [J] . Knowledge-Based Systems . 2020,第Apra6期

机译：基于卷积和改进Elman神经网络的ECG信号中心房颤动和心室扑动的自动检测
4. Calcification Detection in Coronary Artery Disease for Intravascular Ultrasound Images using Convolutional Neural Networks [C] . Hannah Sofian, Joel Chia Ming Than, Suraya Mohamad, IEEE International Conference on Smart Instrumentation, Measurement and Application . 2019

机译：使用卷积神经网络对冠状动脉疾病进行血管内超声图像钙化检测
5. Convolutional neural networks for automated cell detection in magnetic resonance imaging data. [D] . Afridi, Muhammad Jamal. 2017

机译：用于磁共振成像数据中细胞自动检测的卷积神经网络。
6. Original research: Automated interpretation of the coronary angioscopy with deep convolutional neural networks [O] . Toru Miyoshi, Akinori Higaki, Hideo Kawakami, 2020

机译：原始研究：使用深度卷积神经网络自动解释冠状动脉造影
7. MODERATED EPOSTERS1385Longitudinal strain assessment in dilated cardiomyopathy patients using a novel accelerated DENSE sequence1407Simultaneous T1 and T2 cardiac quantification with CABIRIA: initial clinical experience1423Head-to-head comparison of acceleration algorithms in 4-dimensional flow CMR1502Left ventricular function and size evaluated by hybrid cardiac positron emission tomography-magnetic resonance: Intraindividual comparison of left ventricular ejection fraction and ventricular volumes derived by two modalities1510Left Atrium assessed by Cardiovascular Magnetic Resonance at 1.5 and 3 Tesla – age and gender effects1514Comparison of Free Breathing Cardiac MRI Radial technique to the Standard Multi breath-hold cine SSFP CMR technique for the assessment of LV Volumes and Function1536Self-navigated free-breathing isotropic 3D whole heart phase sensitive inversion recovery magnetic resonance without navigator for detection of myocardial infarction1547Assessment of Right Ventricular Strain Using Myocardial Deformation Recovery Semi Automated Technique: Initial Experience and Normal Values1586Tissue tracking myocardial deformation analysis and prediction of left ventricular remodeling in acute myocardial infarction1589Investigating strategies for optimal 31P MRS clinical cardiac at 3T: Initial Results1620Quantitative Criteria for the Diagnosis of the Congenital Absence of Pericardium by Cardiac Magnetic Resonance1632Widespread tissue injury during acute myocardial infarction: evidence from advanced CMR relaxometry1322Computed tomography coronary angiography verSus sTRess cArdiac magneTic rEsonance for the manaGement of sYmptomatic revascularized patients: a cost effectiveness study (STRATEGY study)1339Comparison of low- versus high-dose of gadobutrol for late gadolinium enhancement imaging at 1.5 Tesla: a clinical feasibility study1347Multi-parametric Cardiac Magnetic Resonance for Prediction of Cardiac Complications in Thalassemia Intermedia: a Prospective Multicenter Study1461Prognostic value of Cardiovascular Magnetic Resonance derived indexes of myocardial fibrosis in heart transplant recipients1523The role of CMR in the acute phase of hospitalization: changing paradigms1542Preoperative CMR-based score predict ventricular response after surgical left ventricular reconstruction in ischemic heart failure patients1555Excellent response rate to cardiac resynchronization therapy guided with magnetic resonance imaging1626The ECG as a predictor of arrhythmogenic substrate on Cardiac Magnetic Resonance Imaging in patients undergoing ablation for premature ventricular contractions1649Comparison of T1-mapping at 3.0T CMR and angiographic APPROACH score for area at risk assessment in ST-segment elevation myocardial infarction1340Pathological correlates of left bundle branch disease in patients with non-ischemic cardiomyopathy: a cardiovascular magnetic resonance study1342Myocardial remodelling and fibrosis in nonischaemic dilated cardiomyopathy: insights from cardiovascular magnetic resonance1411The association between fibrosis and contractile dysfunction in hypertrophic cardiomyopathy assessed by cardiovascular magnetic resonance1622Persistent myocardial inflammation due to intramyocardial haemorrhage in reperfused STEMI as a precursor to adverse LV remodelling - insights from multi-parametric mapping1566Semiquantitative analysis of low and high b value DWI for detecting myocardial edema in acute myocarditis1567Value of Cardiac MRI In Detecting Coronary Artery Disease In Newly Diagnosed Systolic Dysfunction1570Usefulness of cardiac magnetic resonance in tuberous sclerosis complex1578Papillary muscles offer further insight into hypertrophied hearts: a cardiovascular magnetic resonance study1627Diagnostic and clinical implications of CMR timing (early versus late) in patients with troponin positive acute coronary syndromes and unobstructed coronary arteries: Table 1. [O] . Upasana Tayal, Alexandros Kallifatidis, P. Garg, 2016

机译：在使用新的扩张型心肌病的患者缓和EPOSTERS1385Longitudinal应变评估加速DENSE sequence1407Simultaneous T1和T2与CABIRIA心脏定量：在4维流动的加速算法初始临床experience1423Head对头比较CMR1502Left心室功能和尺寸由混合心脏正电子发射断层摄影术评价 - 磁性共振：由两个modalities1510Left庭派生左室射血分数和心室体积的个体间的比较，在1.5和3特斯拉评估心血管磁共振 - 免费的年龄和性别effects1514Comparison呼吸心脏MRI径向技术标准的多屏气电影SSFP CMR技术的LV卷和Function1536Self-导航自由呼吸各向同性3D整个心脏相位敏感反转恢复磁共振导航仪没有检测右Ventricu心肌infarction1547Assessment的评估拉尔菌株使用心肌变形恢复半自动技术：初步经验和正常Values1586Tissue跟踪心肌变形分析和预测左室重构急性心肌infarction1589Investigating策略优化31P MRS临床心脏在3T：初始Results1620Quantitative标准的先天缺失的诊断心包心脏磁Resonance1632Widespread组织损伤急性心肌梗死时：证据先进CMR relaxometry1322Computed CT冠状动脉成像与压力心脏磁共振对症的管理吻合血管患者：成本效益研究（战略研究）1339Comparison低与高剂量钆布醇在1.5特斯拉晚钆增强成像的临床可行性，在中间型地贫心脏并发症的预测study1347Multi参数心脏核磁共振的前瞻性德穆尔心血管磁共振的ticenter Study1461Prognostic价值衍生心肌纤维化指标在住院的急性期CMR的心脏移植recipients1523The作用：改变基于CMR-paradigms1542Preoperative比分预测缺血性心脏衰竭patients1555Excellent响应速度外科左心室重建心脏再同步化后心室反应治疗与磁共振imaging1626The ECG导引作为心脏磁共振成像致心律失常性基板的在ST段抬高心肌infarction1340Pathological在风险评估经历在3.0T CMR T1映射的室性早搏contractions1649Comparison和血管造影APPROACH分数区域消融患者的预测左束支传导疾病的患者与非缺血性心肌病相关因素：心血管磁共振study1342Myocardial重塑和纤维化nonischaemic扩张型心肌病：在从在由心血管磁性resonance1622Persistent心肌炎症评估肥厚型心肌病的纤维化和收缩功能障碍之间心血管磁性resonance1411The协会由于心肌内出血景点在再灌注STEMI为先导，以不利的LV重塑 - 从低的多参数mapping1566Semiquantitative分析和高的b值DWI的见解为在心脏MRI检测冠状动脉疾病急性myocarditis1567Value在结节性硬化症complex1578Papillary肌肉初诊收缩期Dysfunction1570Usefulness心脏磁共振检测心肌水肿提供进一步的深入了解肥大心脏：心血管磁共振study1627Diagnostic和CMR定时的临床意义（早期与晚）患者肌钙蛋白阳性的急性冠脉综合征和通畅的冠状动脉：表1。

Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network

摘要

著录项

相似文献

相关主题

期刊订阅