Combinatorial Effect of Various Features Extraction on Computer Aided Detection of Pulmonary Nodules in X-ray CT Images

In this paper, we propose a new method for computer aided detection of pulmonary nodules in X-ray CT images to reduce false positive rate under high true positive rate conditions. An essential part of the method is to extract and combine two novel and effective features from the original CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a Gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, pattern recognition techniques can then be used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method. Key–Words: Computer aided diagnosis, Lung cancer, Pulmonary nodules, Feature extraction, Image recognition, X-ray CT images