The accuracy and efficiency of the lung segmentation are significant to computer-aided detection/diagnosis (CAD/CADx)scheme for pulmonary nodules detection in chest computed tomography (CT) image. And morphology is widely utilizedto characterize the shape of the object in lung segmentation. In this investigation, a multi-stages based approach whichcombines thresholding, connected component analysis and morphology is proposed to achieve a fast and precise lungsegmentation. The presented framework consists of three stages: thorax extraction, lung segmentation and boundaryrefinement. A dataset of CT scans from different equipments and modalities is utilized to evaluate the proposed method.The average dice similarity coefficient (DSC) of the experiments is 0.97 and average time-consuming of each slice is0.64s. The results demonstrate that the proposed method with multi-stages is an efficient and accurate method for lungsegmentation.
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