Lung Cancer Detection using Fusion, CNN and YOLO in MATLAB

Abstract

Abstract: Lung Cancer is one of the major causes of deaths in India. Various data analytics and classification approaches have been used to diagnose and find lung cancer in numerous cases. Lung Cancer can only be cured by early tumour diagnosis because the basis of the diseases is yet unknown, making prevention impossible. In order to classify the existence of lung cancer/tumour in a CT picture and PET image, a lung cancer detection method using image processing and deep learning is applied. Using Fusion technique, we first obtain CT scans, then PET images of the same patient, then combine both images into one. The classification carried out using image feature extraction. As a result, the combined CT and PET scan images of the patient are classified as normal or abnormal. The tumour component of the abnormal photos is the focus of the detecting process. Using YOLO and CNN, an effective strategy to identify lung cancer and its phases is one that also seeks to produce more precise results.