Application of neural networks in prenatal diagnosis of atrioventricular septal defect.

ABSTRACT:

Background

There is no relevant study on landmarks detection, one of the Convolutional Neural Network algorithms, in the field of fetal echocardiography (FE). This study aimed to explore whether automatic landmarks detection could be used in FE correctly and whether the atrial length (AL) to ventricular length (VL) ratio (AVLR) could be used to diagnose atrioventricular septal defect (AVSD) prenatally.

Methods

This was an observational study. Two hundred and seventy-eight four-chamber views in end diastole, divided into the normal, AVSD, and differential diagnosis groups, were retrospectively included in this study. Seven landmarks were labeled sequentially by the experts on these images, and all images were divided into the training and test sets for normal, AVSD, and diffe

SUBMITTER: Zhou X 

PROVIDER: S-EPMC10839271 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature