基于全卷积网络的左心室射血分数自动检测

doi:10.12068/j.issn.1005-3026.2018.11.011

东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (11): 1572-1576.DOI: 10.12068/j.issn.1005-3026.2018.11.011

基于全卷积网络的左心室射血分数自动检测

徐礼胜，张书琪，牛潇，徐阳

(东北大学中荷生物医学与信息工程学院，辽宁沈阳110169)

收稿日期:2017-08-02 修回日期:2017-08-02 出版日期:2018-11-15 发布日期:2018-11-09
通讯作者: 徐礼胜
作者简介:徐礼胜(1975-)，男，安徽安庆人，东北大学教授，博士生导师.冯明杰(1971-)，男，河南禹州人，东北大学副教授; 王恩刚(1962-)，男，辽宁沈阳人，东北大学教授，博士生导师.
基金资助:
国家自然科学基金资助项目(61773110，61374015，61701099);中央高校基本科研业务费专项资金资助项目(N161904002).

Automatic Detection of Left Ventricular Ejection Fraction Based on Fully Convolutional Networks

XU Li-sheng， ZHANG Shu-qi， NIU Xiao， XU Yang

School of Sino-Dutch Biomedical and Information Engineering， Northeastern University， Shenyang 110169， China.

Received:2017-08-02 Revised:2017-08-02 Online:2018-11-15 Published:2018-11-09
Contact: XU Li-sheng
About author:-
Supported by:
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摘要/Abstract

摘要： 提出了一种基于全卷积网络(fully convolutional networks， FCN)的左心室射血分数自动估测的方法.利用全卷积网络对心脏磁共振图像中的左心室进行内轮廓分割，计算心脏左心室在一个心动周期中各时间点的容积，提取左心室舒张末期与收缩末期的容积，最后推导出左心室的射血分数.使用700组图片对全卷积网络进行训练以及440组图片进行测试，并将最后计算结果与美国国立卫生研究院和儿童国家医疗中心提供的射血分数(ejection fraction， EF)金标准进行了对比，计算准确率为89.8%，结果处在合理的误差范围内.

关键词: 全卷积网络, 射血分数, 磁共振图像, 左心室分割

Abstract: An automatic estimation method of left ventricular ejection fraction based on fully convolutional networks(FCN)is proposed. The left ventricle in magnetic resonance images(MRI) of heart is segmented using FCN. Furthermore， the volume of left ventricle can be calculated at each phase in a heart beat cycle. Finally， the volume of end-systolic and end-diastolic are extracted respectively to deduce the left ventricular ejection fraction. 700 sets of images are used for training the networks and 400 sets for testing. The final results agree well with the ejection fraction(EF)gold standard provided by the American National Institutes of Health and Children′s National Medical Center. The accuracy of the proposed method achieves 89.8%， which is within an acceptable range.

Key words: fully convolutional networks(FCN), ejection fraction(EF), magnetic resonance images(MRI), left ventricular segmentation

中图分类号:

TP391.41

徐礼胜，张书琪，牛潇，徐阳. 基于全卷积网络的左心室射血分数自动检测[J]. 东北大学学报:自然科学版, 2018, 39(11): 1572-1576.

XU Li-sheng， ZHANG Shu-qi， NIU Xiao， XU Yang. Automatic Detection of Left Ventricular Ejection Fraction Based on Fully Convolutional Networks[J]. Journal of Northeastern University Natural Science, 2018, 39(11): 1572-1576.

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基于全卷积网络的左心室射血分数自动检测

Automatic Detection of Left Ventricular Ejection Fraction Based on Fully Convolutional Networks

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