A Novel Method of Segmentation and Analysis of CT Chest Images for Early Lung Cancer Detection

Abstract

Lung Cancer is the most common cancer diagnosed worldwide. It causes a higher amount of deaths. For the survival of cancer patients, early detection and treatment are beneficial and effective. Computer-aided diagnosis (CAD) is one of the most effective techniques utilized for image processing for lung cancer detection. Also, it’s the best image-based method for locating tiny nodules which facilitate early diagnosis of lung cancer. In this paper, the authors implemented a proposed CAD model. The proposed model successfully detected a very small tumor sized between 500 -1000 sq mm and can detect a smaller lung tumor than 500 sq mm if present which will enable physicians to early detect and appropriately stage lung cancer.