Automated Detection of Pulmonary Nodules in CT Scans

This project is based on an IEEE paper; Abstract as below; In this paper, we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) examinations. After a segmentation phase based on the robust fuzzy c-means (RFCM) algorithm proposed by Pham, the regions of interest (ROIs) undergo both 2D and 3D morphological analysis in order to distinguish between nodule and blood vessel sections. This paper describes a CAD system for automated detection and diagnosis of lung nodules. We first segment the lung parenchyma based on the Robust Fuzzy C-Means (RFCM) algorithm, which classifies voxels according to both their grey level and their neighbouring voxels. Then we identify the regions of interest (ROIs) and explore them to detect nodules through morphological analysis.