结合改进分水岭和GVF的三维肝脏分割方法

三维肝脏分割是当前医学图像处理的热点问题,如何准确快速地从腹部CT序列中分割出肝脏是肝部病变诊断的基础。针对传统活动轮廓模型对轮廓线敏感、运算量大的问题,改进了传统轮廓线设置方法,并把算法扩展到三维。首先,在一幅腹部CT图片中采用改进的分水岭算法,按照灰度和纹理的相似性原则从一个种子块开始生长出整个肝脏,再用其边缘作为相邻CT序列的起始轮廓,用GVF算法从序列图片中分割出肝脏,重复该过程,直至分割出整个腹部序列图像的切片,进行三维重建。

3D liver segmentation method combined with improved watershed method and GVF

Three-dimensional liver segmentation is a hot issue in medical image processing study. Accurate and fast liver segmentation from abdominal CT sequences is basis for liver lesions diagnose. The traditional active contour model is sen-sitive to contour and has large amount of computation, new method improves traditional contour set, and extends the algo-rithm to three-dimensional. In an abdominal CT image, using improved watershed algorithm to grow a liver from a seed block by the principle of the similarity between gray scale and texture, then using its edge as the start contour of the adjacent CT sequence, with GVF algorithm split a liver from a sequence of images, the process is repeated until getting all slices of the entire abdomen, then 3-D reconstructed.