Detection of Lung Cancer using Image Processing Techniques

Abstract

Image processing techniques are used mostly in many medical areas, where the time factor is very important to discover the abnormality in the target image. As we all are aware, lung cancer is one of the most dangerous and life-taking diseases in the world, recognizing it in the early stages is vital. Though CT scan imaging is the best imaging technique in the medical field, the doctors find it difficult in identifying the lung tumor in the CT scan images due to which the computer-aided diagnosis came into existence. As a result, computer-aided diagnosis (CAD) makes it simple for doctors to precisely identify malignant cells. Many image processing and machine learning-based computer-aided approaches have been developed and applied. We proposed a method to detect cancer tumours in the lungs based on the area in this study. This paper mainly deals with the identification of the lung cancer stage. Initially, the acquired CT scan image is preprocessed and segmented. In the later stages, we compute the area of the separated ROIs and classify them based upon it. The result shows the tumor region and to which type does it belong, whether it is cancerous or non-cancerous.