Extraction algorithm of pulmonary fissures from thin-section CT images based on linear feature detector method

Describes a new automatic extraction algorithm of the pulmonary major and minor fissures from three-dimensional (3-D) chest thin-section images of helical computed tomography (CT). These fissures are used for the analysis of pulmonary conformation and the diagnosis of lung cancer. This algorithm consists mainly of the correction and the emphasis of a 2-D linear shadow. The authors applied the proposed algorithm to 25 sets of CT examinations of 12 patients. The results showed that major and minor fissures can be extracted by the proposed algorithm, without reference to streak artifacts on axial CT images by the beam hardening effect, and the motion artifacts by the cardiac beat.

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