A new approach for lung cancer cell detection using Mumford-shah algorithm

For detecting pleural effusion and pneumothorax, which affect the pleural membranes of the lungs, Computer Aided Diagnosis system (CAD) is proposed. The chest CT slices are initially preprocessed to remove the Gaussian noise by using a sigma filter segmentation technique used here extracts the lungs and the regions affected by pleural effusion using conventional thresholding techniques like Otsu's and iterative thresholding, followed by morphological operations. Mumford shah model is then applied, to segment the lung parenchyma as well as to extract the Region of Interest (ROI). Texture features are next extracted using Spectral texture extraction method from the ROIs, which are used to compute the feature vectors. These are used to train using multi-level slice classifier.