Extraction of pulmonary fissures from HRCT images based on surface curvatures analysis and morphology filters

The objective of the present paper is to extract the pulmonary major and minor fissures from 3D chest thin-section computed tomography (CT) images obtained by helical scan. These fissures are used for the diagnosis of lung cancer and the analysis of pulmonary conformation. We have proposed fissures extraction method without reference to streak artifacts and motion artifacts on the CT images. The new proposed algorithm improves on the previous extraction method using the surface-curvatures analysis for density profile and the morphological filters. The proposed method can also extract pulmonary fissures in contact with the module and the chest walls. We applied the proposed algorithm to 12 patients. The results of our method were more accuracy to extract fissures around pulmonary lesion than by the previous method. The warped fissures extracted by our method show that lesion near fissures is malignancy. Extracted fissures will be aided to diagnose lung cancer and to analyze automatically pulmonary conformation by using computer