3D volumetric CT liver segmentation using hybrid segmentation techniques

SoCPaR 2009 - Soft Computing and Pattern Recognition

Volumn , Issue , 2009, Pages 404-408

  Yussof, Wan Nural Jawahir Wan ^a   Burkhardt, Hans ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

Computed tomography; Hybrid techniques; Liver segmentation

Indexed keywords

ABDOMINAL ORGANS; COMPUTED TOMOGRAPHY; CT SCAN; EUCLIDEAN DISTANCE TRANSFORMS; HYBRID SEGMENTATION; HYBRID TECHNIQUES; LIVER REGIONS; LIVER SEGMENTATION; LIVER TISSUE; MULTISLICE CT; REGION GROWING; REGION-BASED; SEED POINT; VOLUMETRIC CT;

COMPUTER AIDED DIAGNOSIS; COMPUTERIZED TOMOGRAPHY; IMAGE SEGMENTATION; PATTERN RECOGNITION; SOFT COMPUTING; THREE DIMENSIONAL;

LIVER;

EID: 77649295556     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SoCPaR.2009.85     Document Type: Conference Paper

References (8)

1. D. Furukawa and A. Shimizu and H. Kobatake,Automatic Liver Segmentation Method based on Maximum A Posterior Probability Estimation and Level Set Method, T. Heimann, M. Styner, B. van Ginneken (Eds.): 3D Segmentation in The Clinic: A Grand Challenge, 2007, pp. 117-124.
2. E. L. Chen and P. C. Chung, An automatic diagnosis system for CT liver image classification, IEEE Transaction on Biomedical Engineering 45:16, 1998, pp. 783-794.
3. G. Borgefors, Distance transformations in digital images Comput. Vision Graph. Image Process. 34:3, 1986, pp. 344-371.
4. K. S. Seo, Improved fully automatic liver segmentation using histogram tail threshold algorithms, ICCS 2005, 2005, pp. 822-825.
5. S. J. Lim, Y. Y. Jeong and Y. S. Ho, Automatic liver segmentation for volume measurement in CT images, Journal of Visual Communication and Image Representation 17:4, 2006, pp. 860-875.
6. S. Pan and B. M. Dawant, Automatic 3D segmentation of the liver from abdominal CT images: a level set approach, Proceeding of SPIE Medical Imaging 2001: Image Processing 4322, 2001, pp. 128-138
7. T. Heimann and H. P. Meinzer and I. Wolf, A Statistical Deformable Model for the Segmentation of Liver CT Volumes, T. Heimann, M. Styner, B. van Ginneken (Eds.): 3D Segmentation in The Clinic: A Grand Challenge, 2007, pp. 161-166.
8. T. Heimann, B. van Ginneken, M. Styner, Y. Arzhaeva, V. Aurich, C. Bauer, A. Beck, C. Becker, R. Beichel, G. Bekes, F. Bello, G. Binnig, H. Bischof, A. Bornik, P.M.M. Cashman, Y. Chi, A. Cordova, B.M. Dawant, M. Fidrich, J. Furst, D. Furukawa, L. Grenacher, J. Hornegger, D. Kainmueller, R.I. Kitney, H. Kobatake, H. Lamecker, Th. Lange, J. Lee, B. Lennon, R. Li, S. Li, H.-P. Meinzer, G. Nemeth, D.S. Raicu, A.-M. Rau, E.M. van Rikxoort, M. Rousson, L. Rusko, K.A. Saddi, G. Schmidt, D. Seghers, A. Shimizu, P. Slagmolen, E. Sorantin, G. Soza, R. Susomboon, J.M. Waite, A. Wimmer, I. Wolf, Comparison and Evaluation of Methods for Liver Segmentation from CT datasets, IEEE Transactions on Medical Imaging in press. Digital Object Identifier 10.1109/TMI.2009.2013851.