Lung Cancer Detection Using CT Scan Image

Abstract

Lung cancer is the most perilous and widely spread cancer in the world according to stage of discovery of the cancer cells in the lungs. The motivation of this paper is to discover the cancer cells in the lungs at earlier stage. The lung cancer is detected using CAD System which is an interdisciplinary approach based on the techniques of Image Processing and Machine Learning. The forecasting of lung cancer is the most challenging problem, because of the structure of cancer cells, where most of the cells are superimposed. Recently, the image processing techniques are widely used in several medical areas for detection and treatment levels. The time factor is most important to determine the abnormality issues in the targeted image. Image quality and accuracy are the significant factors for quick identification of diseases. Image quality assessment and advancement are depending on the enhancement stage. By using the Image processing techniques like Image enhancement, image segmentation, Feature extraction we can easily identify the tumours in the image. The formulation of a Computer Aided Detection (CAD) system for Lung cancer detection by using an integrative approach based on the techniques of Image Processing and Machine Learning. The lung cancer detection is the extension of the image processing that produces the results of feature extraction and feature selection after segmentation. The system accepts Lung CT (Computed Tomography) images as input. The proposed method is used to detect the cancerous cells effectively from the CT scan images.