Osteoporosis screening from radiographic images has traditionally relied on isolated methods that fail to capture the complex interplay between structural segmentation and diagnostic classification. This paper introduce OMO-Net, a novel multi-output deep learning architecture that simultaneously performs segmentation and classification on metacarpal radiographs to accurately detect osteoporosis. Unlike conventional approaches, OMO-Net integrates a ResNet-50–based feature extractor with dedicated…