Fully automatic extraction of lung parenchyma from CT scans

In this paper, a novel fully automatic method of extraction of lung parenchyma is presented. Combining the iterative gray-level thresholds selection and the pulmonary regions extraction with error detection in 2D image, seed points and threshold are fast determined. In consequence, the pulmonary airspace is detected with 3D region growing method. Two steps airways segmentation with additional shape constrained criterion is used to completely remove airways from the airspace. To avoid lungs adhesion, the connections are detected and located. The dynamic programming method is applied to separate the left lung and right lung. Twelve clinical studies indicate that the novel method can meet the needs for quantification in diagnosis with respect to accuracy and time requirement.