中国卒中杂志2019，Vol.14Issue(5)：437-443,7.DOI:10.3969/j.issn.1673-5765.2019.05.007
基于双流神经网络的颈动脉粥样硬化斑块稳定性区分方法
Method of Distinguishing Stability of Carotid Plaque Based on Two-stream Neural Network
摘要
Abstract
Objective To train two-stream neural network to distinguish the stability of carotid plaques. Methods 844 contrast-enhanced ultrasound videos were used in the experiment. They were from 115 patients with stable carotid plaques and 110 patients with vulnerable carotid plaques verified by pathology after CEA. 744 videos were used as training set to train two-stream network, to find the neural network segment having optimal recognition effect. The left 100 videos were used as test set to distinguish the stability of carotid plaque. Results Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio in training set were 93%, 87%, 97%, 96%, 90%, 29 and 0.13, respectively. The corresponding results in test set were 80%, 70%, 90%, 88%, 75%, 7 and 0.33, respectively. Area under the receiver operating characteristic curve for training set and test set were 0.99 and 0.84 (both P<0.001). Conclusions Training two-stream neural network with contrast-enhanced ultrasound videos with known pathological results of plaques can obtain a model of recognizing the stability of carotid plaques.关键词
颈动脉/斑块/超声造影/双流神经网络Key words
Carotid artery/Plaque/Ultrasonic radiography/Two-stream neural network引用本文复制引用
NING Bin,LI Lu,YU Teng-Fei,TONG Hui,HE Wen,ZHAO Ming-Chang..基于双流神经网络的颈动脉粥样硬化斑块稳定性区分方法[J].中国卒中杂志,2019,14(5):437-443,7.基金项目
北京市医院管理局"扬帆"计划(XMLX201608)国家自然科学基金资助项目(81730050) （XMLX201608）
