基于改进图形切割的三维肺CT肺血管检测

A. Khanna, N. Londhe, Shubhrata Gupta
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引用次数: 1

摘要

三维肺部CT扫描中肺血管的检测是一个非常具有挑战性的问题。血管的识别对临床评价很重要。本文通过设计能量函数,提出了一种基于改进图割算法的血管分割技术。首先,利用自适应k-means算法对增强图像进行建模,给出能量函数的区域参数;然后将改进后的能量函数用于图割算法的血管分割。图割算法利用最小割理论生成图。分割是用VESSEL12站点提供的数据完成的。这种自动分割得到了相当满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of pulmonary vessels in 3D lung CT using improved Graph Cut
The problem of pulmonary vessel detection from 3D pulmonary CT Scan is a very challenging one. The identification of vessels is important for clinical evaluation. In this paper, we proposed a vessel segmentation technique based on improved graph cut algorithm by designing the energy function. First of all, the enhanced image is modeled with adaptive k-means algorithm to give the regional parameter of the energy function. Then the improved energy function is given to graph cut algorithm for vessel segmentation. Graph cut algorithm creates a graph which is cut using minimum cut theory. The segmentation is done with the data provided in VESSEL12 site. This automatic segmentation gives quite satisfactory results.
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