YOLOv8-Based Framework for Accurate Lung CT Nodule Images Detection

Mengzhe Wang

2024

Abstract

Traditional lung Computed Tomography (CT) nodule recognition primarily relies on visual inspection by doctors. However, recent advancements in image recognition models have significantly increased the feasibility of utilizing emerging image recognition models’ powerful capabilities to provide doctors with a new auxiliary means of identifying lung nodules. This study aims to leverage the YOLOv8, a more advanced image processing model, to process the LUNA-16 dataset of lung CT nodule images. Through continuous optimization, the goal is to achieve a relatively ideal recognition accuracy. This paper anticipates evaluating the recognition results from the perspectives of accuracy, recall, and other metrics. By iteratively searching for the local optimal solution of model parameters, the model will be continuously improved. Through final optimization, the study aims to achieve a roughly twofold increase in recognition capability compared to the initial stage, while significantly reducing the false negative rate.

Paper Citation

in Harvard Style

Wang M. (2024). YOLOv8-Based Framework for Accurate Lung CT Nodule Images Detection. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 775-780. DOI: 10.5220/0012972700004508

in Bibtex Style

@conference{emiti24,
author={Mengzhe Wang},
title={YOLOv8-Based Framework for Accurate Lung CT Nodule Images Detection},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={775-780},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012972700004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - YOLOv8-Based Framework for Accurate Lung CT Nodule Images Detection
SN - 978-989-758-713-9
AU - Wang M.
PY - 2024
SP - 775
EP - 780
DO - 10.5220/0012972700004508
PB - SciTePress