Aorta Detection with Fetal Echocardiography Images Using Faster Regional Convolutional Neural Network (R-CNNs)

Abstract

The fetal heart structure has an important role in analyzing the location of abnormalities in the heart. The aorta is one of the fetal heart structures, which has an essential part in exploring how the fetal heart is structured. To see the fetal heart structure can be seen with the help of an echocardiography tool in the form of ultrasound to see ultrasound images of the fetal heart. In ultrasound image data, detection is challenging because of its low image features, shadows, and contrast levels. So that is the first to do it yourself in one of the points of the culture in the culture in the aorta. The approach in this study uses deep learning in cases using Faster Regional Convolutional Neural Network (R-CNNs) with the R-CNNs mask method. The proposed approach has been applied to 151 ultrasound images of the fetal heart for the aortic region. The evaluation results were tested by evaluating metrics on the detection object with an mAP value of 83.71%.