Diagnosis of congenital heart disease in children, namely Atrial Septal Defect (ASD), Atrioventricular Septal Defect (AVSD), and Ventricular Septal Defect (VSD), is hindered by the limited availability of cardiologists in interpreting echocardiography images, necessitating an automated system based on artificial intelligence. This study implements and evaluates a deep learning-based image capti…
Ultrasound (USG) image analysis for detecting Congenital Heart Disease (CHD), such as Atrial Septal Defect (ASD), Ventricular Septal Defect (VSD), and Atrioventricular Septal Defect (AVSD), is still limited by the scarcity of clinical datasets. This study evaluates three Generative Adversarial Network (GAN) architectures, namely Deep Convolutional GAN (DCGAN), Wasserstein GAN with Gradient Pena…