基于多尺度形态学滤波的CT图像疑似肺结节提取

CT图像中疑似结节病灶区域的分割和提取是肺部CAD系统的关键和难点.研究一种基于肺结节几何特征的多尺度形态学滤波的疑似结节区域提取算法,构造了一组不同尺度的类圆形结构元素进行形态学滤波.经过多尺度处理,不同大小的疑似肺结节区域得到增强和突出,气管、血管等线形解剖组织得到了削弱和抑制,结构元素的几何参数及二值化阈值参数的选取不需要人工设置.实验结果表明,该算法可以较好地实现不同大小疑似结节区域的自动提取.

Extraction of Suspected Nodular Lung Lesions Based on Multi-scale Morphology Filtering in Thoracic CT Images

It is hard to segment and extract the suspected nodular lesions from CT images for lung CAD system.To solve the key problem,an extraction algorithm is proposed for the suspected nodular lung lesions area based on the multi-scale morphology filtering which focuses on the feature of tissue geometry.A series of circle-like structure elements with different dimensions are built to do the morphologic filtering.After multi-male processing,all nodules of different sizes are enhanced and stood out from the suspected lung lesion area.On the other hand,such linear tissues as trachea,bronchi tubes and blood-vessels are weakened and suppressed.And a particular advantage of the proposed method is found that the geometric parameters of morphology operator and binary threshold parameters needn't chose manually.Experiment results indicated that the method can extract suspected nodular lesions automatically and effectively.