Automatic extraction of pulmonary fissures from multidetector-row CT images

Abstract

The paper describes the extraction of pulmonary major and minor fissures from three-dimensional (3D) chest multidetector-row computed tomography (MDCT) images. These fissures are used for the diagnosis of lung cancer and the analysis of pulmonary conformation. We have proposed (see Kubo, M. et al, IEEE Trans. Nucl. Sci, vol.46, p.2128-33, 1999) an automatic fissures extraction method using thin-section CT images with much noise. The present study proposes a simpler algorithm to extract fissures using MDCT images with little noise. The new proposed algorithm consists of the highlight method using the VanderBrug operator and the extraction method using morphology filters. We applied the proposed algorithm to one patient. Our method could accurately extract fissures.