Femur Fracture Detection Based on Deep Learning Model YOLOv8

Dongru Xie, Hongjian Yu, Zhijiang Du, Hao Wang, Xiangyu Shen, Zhenyi Wang

2023

Abstract

Femur fracture occurs in various circumstances like car accidents, high-altitude fall incidents, tumour illness, and elderly falls. For better recognition and treatment, physicians need to search the X-ray images for fracture detail. However, some X-ray images were unclear to diagnose, and some were taken from the side position, which is difficult to detect the fracture. This study uses the YOLOv8 model to help physicians with femur fracture detection by utilizing deep-learning models. The performance of YOLOv8 is 42.35% in AP50:95, 84.24% in mAP50, and 25.45% in mAP75 on the private dataset is from Shenzhen University General Hospital. The result shows that the YOLOv8 detection model is competitive and faster on the personal femur fracture dataset than YOLOv3 and YOLOv5 models.

Paper Citation

in Harvard Style

Xie D., Yu H., Du Z., Wang H., Shen X. and Wang Z. (2023). Femur Fracture Detection Based on Deep Learning Model YOLOv8. In Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT; ISBN 978-989-758-677-4, SciTePress, pages 190-193. DOI: 10.5220/0012277300003807

in Bibtex Style

@conference{anit23,
author={Dongru Xie and Hongjian Yu and Zhijiang Du and Hao Wang and Xiangyu Shen and Zhenyi Wang},
title={Femur Fracture Detection Based on Deep Learning Model YOLOv8},
booktitle={Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT},
year={2023},
pages={190-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012277300003807},
isbn={978-989-758-677-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Seminar on Artificial Intelligence, Networking and Information Technology - Volume 1: ANIT
TI - Femur Fracture Detection Based on Deep Learning Model YOLOv8
SN - 978-989-758-677-4
AU - Xie D.
AU - Yu H.
AU - Du Z.
AU - Wang H.
AU - Shen X.
AU - Wang Z.
PY - 2023
SP - 190
EP - 193
DO - 10.5220/0012277300003807
PB - SciTePress