Graph neural network-based breast cancer diagnosis using ultrasound images with optimized graph construction integrating the medically significant features.

Purpose: An automated computerized approach can aid radiologists in the early diagnosis of breast cancer. In this study, a novel method is proposed for classifying breast tumors into benign and malignant, based on the ultrasound images through a Graph Neural Network (GNN) model utilizing clinically significant features.

Method: Ten informative features are extracted from the region of interest (ROI), based on the radiologists' diagnosis markers.