A multistep liver segmentation strategy by combining level set based method with texture analysis for CT images

A multi step liver segmentation method is proposed by combining improved level set based method with texture analysis technique for computed tomography (CT) images in this work. The aiming of proposed algorithm is to overcome the segmentation problem which is caused by similar intensities between liver region and its neighboring tissues, also robust to the variations of shape and size within liver region. Firstly, the total variation with the L1 norm (TV-L1) was used for obtaining the initial liver region, which can make the algorithm more efficient and robust. Secondly, both of global and local energy functions with the level set based method are used for extracting the liver region. Finally, the texture analysis method which is based on gray level co-occurrence matrix (GLCM) was used for refining the liver region boundary. The experimental results on 16 clinical planning CT for radiation therapy were used for demonstrating the efficiency of the proposed method both quantitatively and qualitatively.