Detection and recongnition of pulmonary nodules based on convolution neural network

Qiangchao Shi; Zhibing Shu

doi:10.1117/12.3014478

9 January 2024 Detection and recongnition of pulmonary nodules based on convolution neural network

Qiangchao Shi, Zhibing Shu

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129692E (2024) https://doi.org/10.1117/12.3014478
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

Lung cancer is the disease with the highest incidence rate and mortality of cancer in China, which seriously threatens human life safety. Pulmonary nodules are the main factor leading to lung cancer, and their precise identification plays a crucial role in clinical diagnosis. This paper proposes a lung nodule detection model that combines global image information to address issues. The model is based on improved YOLOV5 network. Finally, comparative experiments have verified the accuracy and effectiveness of this model.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiangchao Shi and Zhibing Shu "Detection and recongnition of pulmonary nodules based on convolution neural network", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129692E (9 January 2024); https://doi.org/10.1117/12.3014478

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