Lung nodule CT medical image analysis based on deep learning

Yuwei Cai; Ruiquan Chen; Hao Liu; Zheng Peng; Yufeng Yuan; Yuan Lu; Xiao Peng

doi:10.1117/12.2652067

20 January 2023 Lung nodule CT medical image analysis based on deep learning

Yuwei Cai, Ruiquan Chen, Hao Liu, Zheng Peng, Yufeng Yuan, Yuan Lu, Xiao Peng

Proceedings Volume 12563, AOPC 2022: AI in Optics and Photonics; 1256308 (2023) https://doi.org/10.1117/12.2652067
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

In recent years, lung cancer has become one of the most lethal factors to human beings. Clinical data show that the probability of lung nodules developed into lung cancer is about 30%. Due to the lack of obvious symptoms, around 70% of lung cancer patients in China are in advanced stage of lung cancer when firstly diagnosed. Therefore, early identification of lung nodules is of great significance for early diagnosis and therapy. Currently, artificial intelligence has been widely used to generate predictive model of lung nodules by learning algorithms adapted to image characteristics, leading to improved accuracy and higher sensitivity of diagnosis of early lung cancer. In this work, Luna16 (lung nodule analysis 2016, containing a total of 888 low-dose chest Computed Tomography (CT) thin-slice plain scan lesions) were selected as the data set, providing a total of 1018 CT slices with the most representative shape of lung nodules in this analysis. Next, this project was performed on Baidu AI Studio platform, applying both U-Net and PSP Net to train a model of rapid detection of lung nodules. The training process generated a model providing a rapid and accurate identification of lung nodules larger than 3 mm in diameter. Results showed that the accuracy of U-Net was higher than that of PSP Net, indicating a high potential in further clinical diagnosis in lung cancer.

Citation Download Citation

Yuwei Cai, Ruiquan Chen, Hao Liu, Zheng Peng, Yufeng Yuan, Yuan Lu, and Xiao Peng "Lung nodule CT medical image analysis based on deep learning", Proc. SPIE 12563, AOPC 2022: AI in Optics and Photonics, 1256308 (20 January 2023); https://doi.org/10.1117/12.2652067

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KEYWORDS

Lung

Lung cancer

Computed tomography

Medical imaging

Image segmentation

Data modeling

X-ray computed tomography

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