SmartUro: An Advanced Deep Learning Framework for Automated Kidney Stone Detection and Classification in Medical Imaging

Kidney stone disease affects 10-15% of the global population, yet traditional diagnostic methods are time-intensive and error-prone. This paper presents SmartUro, an intelligent diagnostic system leveraging YOLOv8 deep learning architecture for automated kidney stone detection across CT, MRI, X-ray, and ultrasound imaging. Our system achieves 93.0% mean Average Precision (mAP50), with 93.8% precision and 92.9% recall, processing images in under 3 seconds. Through multi-dataset integration and systematic optimization, SmartUro demonstrates clinical-grade accuracy suitable for deployment in both well-resourced centers and underserved facilities. A Streamlit-based web interface enables real-time clinical integration with comprehensive diagnostic reporting.