Lung Nodule Detection and Classification by Using Convolutional Neural Network

According to the stud of World Health Organization (WHO), lung cancer is leading cause of death among all types of cancers (L. A. Torre et al., 2015). Lung cancer detection in early stage is became easy with the help of several image processing and machine learning techniques. Artificial Neural Network is proven to be the best technique for medical imaging, especially in lung cancer diagnosis. For lung nodule detection Computer Tomography (CT) scan images are preferred by so many researchers. The lung CT scans are extracted from Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) (Armato III et al., 2015) dataset. To detect lung nodules from CT scans. various image preprocessing techniques such as thresholding, clearing border and some morphological operations such as erosion, closing and opening are applied and after detecting Region of Interest (ROI), Convolutiona I Neural Network (CNN) is used to classify lung nodules using preprocessed images and it has given accuracy as 91.66% and sensitivity as 83%.