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Research Paper | Computer Engineering | India | Volume 13 Issue 1, January 2024

CT Imaging Technology for Lung Cancer Detection: A Mechanism-Based Approach

Amanjot ^[2] | Meenakshi Sharma ^[5]

Abstract: Addressing image classification remains a significant challenge in image pre-processing methodologies. Numerous classification approaches have been developed to tackle this issue. This study introduces a novel classifier, SVM-FA (Support Vector Machine optimized with Firefly Approach), specifically designed for detecting lung cancer based on CT images. Given the critical nature of lung cancer, early analysis of the disease is imperative. To achieve this, the study employs image pre-processing techniques, including filtration and segmentation, on input CT scan images. Subsequently, the SVM classifier optimized with the firefly approach is applied to the pre-processed data with the goal of improving the accuracy of the final prediction. To assess the effectiveness of the proposed SVM-FA approach, a comparative analysis is conducted, comparing it with traditional methods and the standard SVM classifier. The results indicate that the proposed approach is both effective and efficient, achieving a high accuracy rate (98%) and specificity (84%) in comparison to the alternatives.

Keywords: Pre-processing of medical images, Support Vector Machine (SVM) classification, Optimization using Firefly Algorithm, Lung cancer

Edition: Volume 13 Issue 1, January 2024,

Pages: 703 - 706