Automatic Detection of Secundum Atrial Septal Defect in Children Based on Color Doppler Echocardiographic Images Using Convolutional Neural Networks - Hong, Wenjing; Sheng, Qiuyang; Dong, Bin; Wu, Lanping; Chen, Lijun; Zhao, Leisheng; Liu, Yiqing; Zhu, Junxue; Liu, Yiman; Xie, Yixin; Yu, Yizhou; Wang, Hansong; et al. (Frontiers in Cardiovascular Medicine, 2022)
Secundum atrial septal defect (ASD) is one of the most common congenital heart diseases. This study aims to evaluate the feasibility and accuracy of automatic detection of atrial septal defect in children based on color Doppler echocardiographic images using convolutional neural networks.In this study, we propose a fully automatic detection system for atrial septal defect, which includes three stages. The first stage is used to identify four target echocardiographic views (that is, the subcostal view focusing on the atrium septum, the apical four-chamber view, the low parasternal four-chamber view, and the parasternal short-axis view). These four echocardiographic views are most useful for the diagnosis of atrial septal defectclinically. The second stage aims to segment the target cardiac structure and detect candidates for atrial septal defect. The third stage is to infer the final detection by utilizing the segmentation and detection results of the second stage.The proposed ASD detection system was developed and validated using a training set of 4,031 cases containing 370,057 echocardiographic images and an independent test set of 229 cases containing 203,619 images, of which 105 cases with atrial septal defect and 124 cases with intact atrial septum. Experimental results showed that the proposed ASD detection system achieved the image-level averages of recall, precision, specificity and F1 score of 0.8545, 0.8577, 0.9136 and 0.8546 from the four most clinically useful echocardiographic views, respectively. The proposed system can automatically and accurately identify ASD, laying a good foundation for the subsequent artificial intelligence diagnosis of congenital heart diseases.