Cross-Dataset Generalization Analysis of Transfer Learning Models for Osteoporosis Classification Using Knee X-ray Images

Deep learning techniques have shown promising results for osteoporosis classification using radiograph images. However, the real-world applicability is overestimated by most of the existing studies as they evaluated their model only on a single dataset. To address this limitation, this study investigates the cross-dataset generalization performance of transfer learning models, ranging from lightweight to heavyweight CNN architectures, for knee osteoporosis classification using X-ray images.The study provides insights into the generalization capability of different types of deep learning architectures and may help researchers select suitable models for future osteoporosis classification and medical image analysis tasks.