Towards Transparent AI in Medical Imaging: Fracture Detection in Hand Radiographs with Grad-CAM Insights

Mustafa Juzer Fatehi, Siddharath Malavalli Nagesh, Mandalam Akshit Rao, Stellin John George, J. Jothi, Elakkiya Rajasekar

2025

Abstract

Timely and accurate detection of bone fractures in hand radiographs, particularly in fingers and wrists remains a critical challenge in clinical diagnostics due to anatomical complexity and subtle fracture patterns. This study presents an explainable AI framework for automatic fracture detection using a single-shot detection framework-YOLOv5 Medium (YOLOv5m) model, optimized through targeted preprocessing and interpretability techniques. A dedicated preprocessing pipeline is used to enhance fracture visibility and reduce irrelevant noise. This includes key steps like histogram equalization, Gaussian filtering, Laplacian filtering, and intensity normalization. To foster clinical trust and transparency, we integrate Gradient-weighted Class Activation Mapping (Grad-CAM) to visualize regions of interest influencing the model’s predictions. Trained on a curated dataset of over 9,000 annotated X-ray images, YOLOv5m achieved outstanding performance, with a mean Average Precision mAP@50 of 95.87% and an inference speed of 690 ms, making it suitable for real-time diagnostic support. This work demonstrates the potential of AI-assisted systems not only to improve fracture diagnosis but also to bridge the trust gap in clinical deployment through transparent decision-making support.

Paper Citation

in Harvard Style

Fatehi M., Nagesh S., Rao M., George S., Jothi J. and Rajasekar E. (2025). Towards Transparent AI in Medical Imaging: Fracture Detection in Hand Radiographs with Grad-CAM Insights. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 39-48. DOI: 10.5220/0013676200004000

in Bibtex Style

@conference{kdir25,
author={Mustafa Fatehi and Siddharath Nagesh and Mandalam Rao and Stellin George and J. Jothi and Elakkiya Rajasekar},
title={Towards Transparent AI in Medical Imaging: Fracture Detection in Hand Radiographs with Grad-CAM Insights},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={39-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013676200004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Towards Transparent AI in Medical Imaging: Fracture Detection in Hand Radiographs with Grad-CAM Insights
SN -
AU - Fatehi M.
AU - Nagesh S.
AU - Rao M.
AU - George S.
AU - Jothi J.
AU - Rajasekar E.
PY - 2025
SP - 39
EP - 48
DO - 10.5220/0013676200004000
PB - SciTePress