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2010 International Conference on Complex, Intelligent and Software Intensive Systems
Automatic Volumetric Liver Segmentation Using Texture Based Region Growing
Krakow, Poland
February 15-February 18
ISBN: 978-0-7695-3967-6
| ASCII Text | x | ||
| Orazio Gambino, Salvatore Vitabile, Giuseppe Lo Re, Giuseppe La Tona, Santino Librizzi, Roberto Pirrone, Edoardo Ardizzone, Massimo Midiri, "Automatic Volumetric Liver Segmentation Using Texture Based Region Growing," 2010 International Conference on Complex, Intelligent and Software Intensive Systems, pp. 146-152, 2010 International Conference on Complex, Intelligent and Software Intensive Systems, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/CISIS.2010.118, author = {Orazio Gambino and Salvatore Vitabile and Giuseppe Lo Re and Giuseppe La Tona and Santino Librizzi and Roberto Pirrone and Edoardo Ardizzone and Massimo Midiri}, title = {Automatic Volumetric Liver Segmentation Using Texture Based Region Growing}, journal ={2010 International Conference on Complex, Intelligent and Software Intensive Systems}, volume = {0}, year = {2010}, isbn = {978-0-7695-3967-6}, pages = {146-152}, doi = {http://doi.ieeecomputersociety.org/10.1109/CISIS.2010.118}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2010 International Conference on Complex, Intelligent and Software Intensive Systems TI - Automatic Volumetric Liver Segmentation Using Texture Based Region Growing SN - 978-0-7695-3967-6 SP146 EP152 A1 - Orazio Gambino, A1 - Salvatore Vitabile, A1 - Giuseppe Lo Re, A1 - Giuseppe La Tona, A1 - Santino Librizzi, A1 - Roberto Pirrone, A1 - Edoardo Ardizzone, A1 - Massimo Midiri, PY - 2010 KW - Segmentation KW - liver KW - lesion KW - region growing KW - texture analysis KW - GLCM VL - 0 JA - 2010 International Conference on Complex, Intelligent and Software Intensive Systems ER - | |||
In this paper an automatic texture based volumetric region growing method for liver segmentation is proposed. 3D seeded region growing is based on texture features with the automatic selection of the seed voxel inside the liver organ and the automatic threshold value computation for the region growing stop condition. Co-occurrence 3D texture features are extracted from CT abdominal volumes and the seeded region growing algorithm is based on statistics in the features space. Each CT volume is composed by 230 slices, having 512 x 512 pixels as spatial resolution, and 12-bit gray level resolution. In this initial feasible study, 5 healthy volunteer acquisitions has been used. Tests have been performed on both basal phase and arterial phase images. Segmentation result shows the effectiveness of the proposed method: liver organ is correctly recognized and segmented, leaving out liver vessels form the segmented area and overcoming the “organ-splitting” problem. The goodness of the proposed method has been confirmed by manual liver segmentation results, having analogous and super-imposable behavior.
Index Terms:
Segmentation, liver, lesion, region growing, texture analysis, GLCM
Citation:
Orazio Gambino, Salvatore Vitabile, Giuseppe Lo Re, Giuseppe La Tona, Santino Librizzi, Roberto Pirrone, Edoardo Ardizzone, Massimo Midiri, "Automatic Volumetric Liver Segmentation Using Texture Based Region Growing," cisis, pp.146-152, 2010 International Conference on Complex, Intelligent and Software Intensive Systems, 2010
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