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Automatic Lung Segmentation in Chest CT Image Using Morphology

机译:使用形态学在胸部CT图像中自动进行肺分割

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摘要

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.
机译:肺分割的准确性和效率对计算机辅助检测/诊断(CAD / CADx)至关重要 胸部计算机断层扫描(CT)图像中检测肺结节的方案。形态学被广泛利用 以在肺部分割中表征对象的形状。在这项调查中,采用了一种基于多阶段的方法 结合阈值分析,关联成分分析和形态学,以实现快速,精确的肺 分割。提出的框架包括三个阶段:胸廓提取,肺分割和边界 细化。来自不同设备和方式的CT扫描数据集可用于评估所提出的方法。 实验的平均骰子相似系数(DSC)为0.97,每个切片的平均耗时为 0.64秒。结果表明,所提出的多阶段方法是一种高效,准确的肺部治疗方法。 分割。

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