Liver Segmentation in CT Images Using Chan-Vese Model

Liver segmentation in computerized tomography (CT) images has been widely studied in recent years, which generally focuses on segmentation accuracy and processing speed. Of which active models demonstrate a great potential in this field. This paper presents an approach based on Chan-Vese model and other techniques. Firstly, the basic theory on Chan-Vese model is introduced. Secondly, a pre-processing method using Gaussian function is employed to get liver likelihood images for segmentation. Thirdly, an improved Chan-Vese model is proposed to optimize the contour evolution when segmenting each CT slice. Finally, the superior liver region is extracted by applying morphologic operation together with priori knowledge. Experiments on a variety of CT images show its effectiveness and efficiency.

[1]  Thomas Lange,et al.  Automatic segmentation of the liver for preoperative planning of resections. , 2003, Studies in health technology and informatics.

[2]  Hochul Kim,et al.  Resolving the Initial Contour Problem of GVF Snake in the Sequential Images , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[4]  Isabelle Bloch,et al.  Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation , 2004, Real Time Imaging.

[5]  Jong-An Park,et al.  Improved Automatic Liver Segmentation of a Contrast Enhanced CT Image , 2005, PCM.

[6]  Xiangrong Zhou,et al.  Construction of a probabilistic atlas for automated liver segmentation in non-contrast torso CT images , 2005 .

[7]  Benoit M. Dawant,et al.  Automatic 3D segmentation of the liver from abdominal CT images: a level-set approach , 2001, SPIE Medical Imaging.

[8]  Yo-Sung Ho,et al.  Automatic liver segmentation for volume measurement in CT Images , 2006, J. Vis. Commun. Image Represent..

[9]  Krishna Subramanyan,et al.  Semi-automatic procedure to extract Couinaud liver segments from multislice CT data , 2003, SPIE Medical Imaging.

[10]  Chunming Li,et al.  Level set evolution without re-initialization: a new variational formulation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[11]  Gabriele Lombardi,et al.  Automatic liver segmentation from abdominal CT scans , 2007, 14th International Conference on Image Analysis and Processing (ICIAP 2007).