Computer-aided classification of lung nodules on CT images with expert knowledge

Chuangye Wan; Ling Ma; Xiabi Liu; Baowei Fei

doi:10.1117/12.2581888

15 February 2021 Computer-aided classification of lung nodules on CT images with expert knowledge

Chuangye Wan, Ling Ma, Xiabi Liu, Baowei Fei

Proceedings Volume 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling; 115982K (2021) https://doi.org/10.1117/12.2581888
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

Accurate classification of pulmonary nodules in the CT images is critical for early detection of lung cancer as well as the assessment of the effect from COVID-19. In this paper, we propose a computer-aided classification method for lung nodules using expert knowledge. We use a decoupling metric learning model to describe the deep characteristics of the nodules and then calculate the similarity between the current nodule and the nodules in the database. By analyzing the returned nodules with the diagnosis information, we obtain the expert knowledge of similar nodules, based on which we make the decision of the current nodule. The proposed method has been evaluated on the benchmark LIDC-IDRI dataset and achieved an accuracy of 95.7% and AUC of 0.9901. The proposed classification method can have a variety of applications in lung cancer detection, diagnosis and therapy.

Conference Presentation

Citation Download Citation

Chuangye Wan, Ling Ma, Xiabi Liu, and Baowei Fei "Computer-aided classification of lung nodules on CT images with expert knowledge", Proc. SPIE 11598, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, 115982K (15 February 2021); https://doi.org/10.1117/12.2581888

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