Design and analysis of automated lung cancer detection using convolution neural network in MATLAB

Ramli, Nur Farah Nadia (2025) Design and analysis of automated lung cancer detection using convolution neural network in MATLAB. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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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 Dataset in Kaggle, which contains 287 lung images in which 161 cancer lung images and 126 non-cancer images. The proposed model classify the lung CT images as cancerous or normal image accurately with 97.67% accuracy, 96% of sensitivity and 94%. of specificity.

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