Lung Cancer Detection through Image Analysis Techniques Applied to CT Scans

This research paper aims to present and discuss the utilization of image analysis techniques for the detection of lung cancer through CT scans. Region growing, edge detection, and thresholding are explored as image analysis techniques for the identification of abnormal regions that may indicate tumors. All techniques were implemented and tested using a dataset of lung images, with overlapping regions examined for increased accuracy in tumor identification. The research aims to prove that utilizing multiple image processing techniques may increase the accuracy of tumor identification, providing a computational tool for radiologists for early tumor detection.