腹部CT图像序列中的肝脏分割

Liver segmentation on abdominal CT images

摘要:

针对腹部CT图像肝脏区域提取问题,提出了一种新的基于阈值法和改进的广义梯度矢量流-蛇(GGVF-Snake)模型的分割方法．首先,采用Window-Leveling算法将CT图像转换为灰度图像,突出肝脏区域,通过改进的曲率各向异性扩散滤波器对图像进行平滑滤波;其次,利用阈值法获取肝脏的初始轮廓;最后,基于改进的GGVF-Snake模型对初始轮廓进行调整得到更加平滑和精确的肝脏轮廓．通过不同的腹部CT图像序列中肝脏的分割结果表明,该方法能高效、精确的提取肝脏区域,满足临床应用的需求．

Abstract:

For liver segmentation on abdominal CT images, a novel algorithm is proposed which is based on the threshold method and modified GGVF-Snake model. Firstly, the CT image is converted into grayscale by using Window-Leveling algorithm, and then Modified Curvature anisotropic diffusion filter is applied. Secondly, a threshold method is used to obtain the initial contour of liver. Finally, the accurate liver boundary is obtained by using a modified GGVF-Snake model. Experimental results show that the proposed algorithm can be applied to the segmentation of liver on abdominal CT images effectively.