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Detection of Lung Cancer Using Convolution Neural Network

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Abstract

In the modern world, one of the most prevalent and hazardous cancers is the lung cancer disease that causes the most fatalities each year. Accurate lung cancer identification could increase endurance rates. In this research work, a computer aided system for detecting lung cancer using convolution neural network (CNN) is proposed. The proposed model includes preprocessing, image segmentation model training, and tumor classification. The model is based on the Lung Image Database Consortium (LIDC), which contains 5200 lung images in which 3400 cancer lung images and 1800 non cancer images. The proposed model classify the lung CT images as cancerous or normal image accurately with 92.96% accuracy, 97.45% of sensitivity and 86.08%. of specificity.

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Authors and Affiliations

  1. Faculty of Engineering and Technology, Jain University, Bengaluru, Karnataka, 562112, India

    C. Shankara & S. A. Hariprasad

  2. Vidyavardhaka College of Engineering, Mysuru, Karnataka, 560027, India

    D. U. Latha

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  1. C. Shankara
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  2. S. A. Hariprasad
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  3. D. U. Latha
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Correspondence to C. Shankara.

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This article is part of the topical collection “Advances in Computational Intelligence for Artificial Intelligence, Machine Learning, Internet of Things and Data Analytics” guest edited by S. Meenakshi Sundaram, Young Lee and Gururaj K S.

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Shankara, C., Hariprasad, S.A. & Latha, D.U. Detection of Lung Cancer Using Convolution Neural Network. SN COMPUT. SCI. 4, 225 (2023). https://doi.org/10.1007/s42979-022-01630-y

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