Congenital heart disease in children requires accurate early detection through ultrasonography (USG) imaging. This study aims to develop a deep learning–based system for view classification and hole segmentation in pediatric cardiac images. A Vision Transformer (ViT) model was employed to classify five cardiac views (4CH, 5CH, LA, SA, and SUB), while segmentation was performed using YOLO11-se…