摘要
肝脏肿瘤组织边缘模糊不清和凹凸多变,传统的基于区域和基于边界的算法提取肝脏肿瘤区域很困难。本文介绍了Poisson Matting算法,该方法将透明度(α值)作为图像的一种内在属性,变分地寻求其最优解,达到目标提取的目的。同时将其应用到肝癌CT图像分割结果,并针对Poisson算法中,程序运行时间比较长的问题,对算法中耗用时间多的两个步骤:图像初始α值的计算以及前景图像F、背景图像B的计算进行了改进,取得了比较理想的效果。
It is very difficult to use the conventional methods that are based on area and on border for extracting a region of intered such as liver tumor region with vague and irregular boundaries. This paper introduces Poisson matting that uses transparency （α value） as self-property of image and seeks its best result value to achieve the aim of extracting object. Meanwhile, this method is applied to the liver tumor CT picture experimental results. It makes improvement in two steps： computing image source α value, calculating foreground image F and background image B. Consequently, successful result is obtained.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2009年第4期735-738,共4页
Journal of Biomedical Engineering
关键词
透明度(α通道)
肝癌
目标提取
边界区域
Transparency （α channel）
Liver tumor
Object extraction
Boundary region
