基于欧氏距离变换的肺部粘连肿瘤分割算法

以肺部CT图像为研究对象,针对肺部粘连肿瘤图片本身的特点,提出了一种基于边缘跟踪的二维欧氏距离变换算法.从目标区域的最外层边界开始,自外向内对目标区域进行边缘跟踪、腐蚀,直到肿瘤区粘连部分与肺部边界分离.算法能够计算精确的欧氏距离.通过实验分割出的肿瘤和放射科医生手工勾画的肿瘤轮廓对比,5幅病例图像重叠率达到了75%左右,实验结果表明该方法对于中晚期肺部粘连肿瘤的分割有一定的效果.

Segmentation of attached tumor in lung based on Euclidean distance transform

Targeting at lung CT image,aiming at the basis characteristics of attached tumor,a 2D Euclidean distance transform algorithm based on contour tracking is presented.Beginning with the outest layer,the algorithm tracks and erodes the contour of the object from outer to inner,until to the division between the zone of attached tumor and the contour of lung.This algorithm produces perfect Euclidean distance.By comparing the segmentation tumor by experiments and the tumor outlined by radiation doctors,the overlap...