Abstract
Machine learning techniques for medical imaging have attracted a lot of attention in recent years. Detecting lung tumors with CT scans is an area that has gained a lot of interest. Unlike many computer-aided detection methods that rely on either CT or PET images alone, this study proposes a novel method that combines both types of scans for lung cancer detection. Tumor cells of benign or malignant nature in the lungs cause lung cancer to develop. Benign tumor cells are the ones that can grow without harming the surrounding healthy cells. Malignant cells can grow very large and spread to other healthy cells, making the situation worse. The objective of this research study is to distinguish various kinds of cells and identify tumors at preliminary stages. The detection of benign or malignant tumor cells is done using deep learning techniques such as CNN and KGBA.