Improving YOLO Efficient for Knee Osteoarthritis Detection Using Minkowski Distance - Fadhil Najim, Marwah; Alrammahi, Atheer; Mohsen Mahdi, Ahmed (Journal of Al-Qadisiyah for Computer Science and Mathematics, 2025)
This study presents an enhanced YOLO-based deep learning model for automatic detection of knee osteoarthritis (KOA) from X-ray images. The integration of Minkowski distance into the loss function improves the model’s sensitivity to spatial variations and noise. Extensive preprocessing and a lightweight YOLO architecture ensure real-time performance with high accuracy. Experimental results demonstrate superior detection rates compared to traditional methods, especially in identifying early-stage KOA.