Automated Bone Fracture Detection System Using YOLOv7 with Secure Email Data Sharing

Swarada Gade, Vashita Nukala, Tanaya Sutar, Shravani Walunj, Avinash Golande, Amruta Hingmire, Vinodkumar Bhutnal

2025

Abstract

The demand for more precise and timely bone fractures diagnosis grew resulting in integration of advanced technologies to medical imaging. This paper describes the development and realization of a deep learning system for automatic detection of bone fractures in X-ray images, which uses YOLOv7 model for improved diagnostic accuracy and efficiency. A secure mechanism to transmit medical images and reports through email is included in the system. Furthermore, this system supports direct downloading of DICOM images as well as creating simple diagnostic reports automatically thus taking out serial steps that increase delay time for patient feedback. This innovative approach leverages cutting-edge deep learning techniques to address critical healthcare needs, streamline diagnostic workflows, and enhance patient outcomes. Real-time fracture detection in the YOLOv7 model is possible because of its use of data augmentation methods during the process of training, which assures robustness and reliability in different scenarios. Through the systematic methodology of data preparation, model training, and evaluation defined in this framework, the potential of the system as a reliable asset in clinical applications is demonstrated. The proposed model minimized the dependency on manual procedures, maximized the speed of clinical decisions, and reinstated decision processes through standardized results. Hence, this framework serves as a noble contribution to modern medical diagnostics.

Paper Citation

in Harvard Style

Gade S., Nukala V., Sutar T., Walunj S., Golande A., Hingmire A. and Bhutnal V. (2025). Automated Bone Fracture Detection System Using YOLOv7 with Secure Email Data Sharing. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 538-549. DOI: 10.5220/0013624300004664

in Bibtex Style

@conference{incoft25,
author={Swarada Gade and Vashita Nukala and Tanaya Sutar and Shravani Walunj and Avinash Golande and Amruta Hingmire and Vinodkumar Bhutnal},
title={Automated Bone Fracture Detection System Using YOLOv7 with Secure Email Data Sharing},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={538-549},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013624300004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Automated Bone Fracture Detection System Using YOLOv7 with Secure Email Data Sharing
SN - 978-989-758-763-4
AU - Gade S.
AU - Nukala V.
AU - Sutar T.
AU - Walunj S.
AU - Golande A.
AU - Hingmire A.
AU - Bhutnal V.
PY - 2025
SP - 538
EP - 549
DO - 10.5220/0013624300004664
PB - SciTePress