Integration of Morphology and Graph-based Techniques for Fully Automatic Liver Segmentation

Here a fully 3D algorithm for automatic liver segmentation from CT volumetric datasets is presented. The algorithm starts by smoothing the original volume using anisotropic diffusion. The coarse liver region is obtained from the threshold process that is based on a priori knowledge. Then, several morphological operations is performed such as operating the liver to detach the unwanted region connected to the liver and finding the largest component using the connected component labeling (CCL) algorithm. At this stage, both 3D and 2D CCL is done subsequently. However, in 2D CCL, the adjacent slices are also affected from current slice changes. Finally, the boundary of the liver is refined using graph-cuts solver. Our algorithm does not require any user interaction or training datasets to be used. The algorithm has been evaluated on 10 CT scans of the liver and the results are encouraging to poor quality of images.

[1]  Yeong-Gil Shin,et al.  Efficient liver segmentation using a level-set method with optimal detection of the initial liver boundary from level-set speed images , 2007, Comput. Methods Programs Biomed..

[2]  Thomas Lange,et al.  A Statistical Shape Model for the Liver , 2002, MICCAI.

[3]  Yussof W.N.J.W.,et al.  3D LIVER SEGMENTATION USING HYBRID SEGMENTATION TECHNIQUES , 2009 .

[4]  Hans-Peter Meinzer,et al.  A Statistical Deformable Model for the Segmentation of Liver CT Volumes , 2007 .

[5]  Guido Gerig,et al.  Nonlinear anisotropic filtering of MRI data , 1992, IEEE Trans. Medical Imaging.

[6]  Martin Styner,et al.  Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets , 2009, IEEE Transactions on Medical Imaging.

[7]  Volker Aurich,et al.  HepaTux - A Semiautomatic Liver Segmentation System , 2007 .

[8]  Hans Burkhardt,et al.  3D Anisotropic Diffusion for Liver Segmentation , 2009 .

[9]  Li Ma,et al.  Liver Segmentation Based on Expectation Maximization and Morphological Filters in CT Images , 2007, 2007 1st International Conference on Bioinformatics and Biomedical Engineering.

[10]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[11]  Gareth Funka-Lea,et al.  Graph Cuts and Efficient N-D Image Segmentation , 2006, International Journal of Computer Vision.

[12]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[13]  Akinobu Shimizu,et al.  Automatic Liver Segmentation Method based on Maximum A Posterior Probability Estimation and Level Set Method , 2007 .

[14]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[15]  Touradj Ebrahimi,et al.  MESH: measuring errors between surfaces using the Hausdorff distance , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

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

[17]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[18]  Adel Elmaghraby,et al.  AN ACTIVE SURFACE FOR VOLUMETRIC IMAGE SEGMENTATION , 2009 .

[19]  Lin-Lin Huang,et al.  Liver segmentation for CT images using an improved GGVF-snake , 2007, SICE Annual Conference 2007.

[20]  B. Ginneken,et al.  3D Segmentation in the Clinic: A Grand Challenge , 2007 .

[21]  William M. Wells,et al.  Medical Image Computing and Computer-Assisted Intervention — MICCAI’98 , 1998, Lecture Notes in Computer Science.

[22]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

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

[24]  Elena Casiraghi,et al.  Liver segmentation from computed tomography scans: A survey and a new algorithm , 2009, Artif. Intell. Medicine.

[25]  Leo Joskowicz,et al.  An iterative Bayesian approach for nearly automatic liver segmentation: algorithm and validation , 2008, International Journal of Computer Assisted Radiology and Surgery.

[26]  Raffi Enficiaud.  Algorithmes multidimensionnels et multispectraux en Morphologie Mathématique : approche par méta-programmation. , 2007 .

[27]  E-Liang Chen,et al.  An automatic diagnostic system for CT liver image classification , 1998, IEEE Transactions on Biomedical Engineering.

[28]  Shaohui Huang,et al.  Using GVF Snake to Segment Liver from CT Images , 2006, 2006 3rd IEEE/EMBS International Summer School on Medical Devices and Biosensors.