Segmentation of liver vasculature from contrast enhanced CT images using context-based voting

IEEE Transactions on Biomedical Engineering

Volumn 58, Issue 8, 2011, Pages 2144-2153

  Chi, Yanling ^a   Liu, Jimin ^a   Venkatesh, Sudhakar K ^b   Huang, Su ^a   Zhou, Jiayin ^c   Tian, Qi ^c   Nowinski, Wieslaw L ^a,d  

^a AGENCY FOR SCIENCE   (Singapore)

^b NATIONAL UNIVERSITY HOSPITAL   (Singapore)

^c INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^d UNIVERSITY OF WASHINGTON MEDICAL CENTER   (United States)

Author keywords

Liver vasculature segmentation; multiple feature point voting; vessel context; vessel junction measure

Indexed keywords

CONTEXT INFORMATION; CONTEXT-BASED; CONTRAST-ENHANCED CT; CT IMAGE; DATA SETS; DUAL CORE PROCESSORS; MULTIPLE FEATURES; SEGMENTATION ACCURACY; THIRD-ORDER; VASCULATURE; VASCULATURE SEGMENTATION; VESSEL CONTEXT; VESSEL JUNCTION; VESSEL SEGMENTATION; VOTING MECHANISM;

COMPUTERIZED TOMOGRAPHY;

IMAGE SEGMENTATION;

ARTICLE; BLOOD VESSEL; COMPUTER ASSISTED TOMOGRAPHY; HEPATIC ARTERY; HEPATIC VEIN; HUMAN; IMAGE ANALYSIS; LIVER; LIVER SURGERY; LIVER TUMOR; PORTAL VEIN; THREE DIMENSIONAL IMAGING; TREATMENT PLANNING; TUMOR VOLUME; ALGORITHM; ANGIOGRAPHY; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; PROCEDURES;

CONTRAST MEDIUM;

ALGORITHMS; ANGIOGRAPHY; ARTIFICIAL INTELLIGENCE; CONTRAST MEDIA; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; PORTAL VEIN; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 79960733564     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2010.2093523     Document Type: Article

References (24)

1. K. Valji, Vascular and Interventional Radiology. vol. 10, Philadelphia, PA: W. B. Saunders Company, 1999, pp. 204-237.
2. C. K. Wong and C. S. Chung, "Probabilistic vessel axis tracing and its application to vessel segmentation with stream surfaces and minimum cost paths," Med. Image Anal, vol. 11, pp. 567-587, 2007.
3. R. Manniesing, B. K. Velthuis, M. S. Leeuwen, I. C. Schaaf, P. J. Laar, and W. J. Niessen, "Level set based cerebral vasculature segmentation and diameter quantification in CT angiography," Med. Image Anal, vol. 10, pp. 200-214, 2006. (Pubitemid 43174974)
4. A. Gooya, L. Hongen, K. Matsumiya, K. Masamune, Y. Masutani, and T. Dohi, "A variational method for geometric regularization of vascular segmentation in medical images," IEEE Trans. Image Process, vol. 17, no. 8, pp. 1295-1312, Aug. 2008.
5. C. Florin, N. Paragios, and J. Williams, "Particle filters, a quasi-Monte Carlo solution for segmentation of coronaries," in Proc. Int. Conf. Med. Image Comput. Comput.-AssistedIntervention, 2005, pp. 246-253. (Pubitemid 43828257)
6. S. D. Olabarriaga, M. Breeuwer, and W. J. Niessen, "Minimum cost path algorithm for coronary artery central axis tracking in CT Images," in Proc. Int. Conf. Med. Image Comput. Comput.-Assisted Intervention, 2003, vol. 2879, pp. 687-694.
7. P. H. Kitslaar, M. Frenay, E. Oost, J. Dijkstra, B. Stoe, and J. Reiber, "Con-nected component and morpholgy based extraction of arterial centerlines of the heart," in Proc. Int. Conf. Med. Image Comput. Comput.-Assisted Intervention, 2008.
8. A. Szymczak, A. Stillman, A. Tannenbaum, and K. Mischaikow, "Coronary vessel trees from 3D imagery: A topological approach," Med. Image Anal, vol. 10, pp. 548-559, 2006. (Pubitemid 44161154)
9. D. Lesage, E. D. Angelini, I. Bloch, and G. F. Lea, "A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes," Med. ImageAnal., vol. 13, pp. 819-845, 2009.
10. O. Friman, M. Hindennach, C. Kuhnel, and H.-O. Peitgen, "Multiple hypothesis template tracking of small 3D vessel structures," Med. Image Anal, vol. 14, pp. 160-171, 2010.
11. S. Esneault, C. Lafon, and J.-L. Dillenseger, "Liver vessels segmentation using a hybrid geometrical moments/graph cuts method," IEEE Trans. Biomed. Eng., vol. 57, no. 2, pp. 276-283, Feb. 2010.
12. C. Bauer, T. Pock, E. Sorantin, H. Bischof, and R. Beichel, "Segmentation of interwoven 3d tubular tree structures utilizing shape priors and graph cuts," Med. Image Anal, vol. 14, pp. 172-184, 2010.
13. D. Shaked and A. M. Bruckstein, "Pruning medial axes," Comput. Vis. Image Understanding, vol. 69, pp. 156-169, 1998. (Pubitemid 128428639)
14. O. C. Eidheim, L. Aurdal, T. O. Jensen, T. Mala, and B. Edwin, "Segmentation of liver vessels as seen in MR and CT images," Int. J. Comput.-Assisted Radiol. Surg., vol. 1268, pp. 201-206, 2004.
15. D. Selle, B. Preim, A. Schenk, andH.-O. Peitgen, "Analysis of vasculature for liver surgical planning," IEEE Trans. Med. Imag, vol. 21, no. 11, pp. 1344-1357, 2002.
16. Y. Chi andM. K. H. Leung, "Ageneral shape contextframeworkfor object identification," Comput. Vis. Image Understanding, vol. 12, pp. 324-336, 2008.
17. http://www.liversuite.com, 2010.
18. A. F. Frangi, W. J. Nissen, K. L. Vincken, and M. A. Viergever, "Multiscale vessel enhancement filtering," in Proc. Int. Conf. Med. Image Comput. Comput.-AssistedIntervention, 1998, pp. 130-137. (Pubitemid 128152655)
19. G. Medioni, C. K. Tang, and M. S. Lee, "Tensor voting: Theory and applications," in Proc. RFIA, 2000.
20. http://www.cs.otago.ac.nz/cosc453/student-tutorials/principal-components. pdf, 2002.
21. T. S. Yoo, M. J. Ackerman, W. E. Lorensen, W. Schroeder, V. Chalana, S. Aylward, D. Metaxes, and R. Whitaker, "Engineering and algorithm design for an image processing API: A technical report on ITK-The Insight Toolkit," in Proc. Medicine Meets Virtual Reality, J. Westwood, ed., Amsterdam: IOS Press, 2002, pp. 586-592.
22. J. Serra, Image Analysis and Mathematical Morphology. New York: Academic, 1982.
23. A. M. Mendonca and A. Campilho, "Segmentation ofretinal blood vessels by combining the detection of centerlines and morphological reconstruc-tion," IEEE Trans. Med. Imag., vol. 25, no. 9, pp. 1200-1213, Sep. 2006. (Pubitemid 44304279)
24. L. Antiga, M. Piccinelli, L. Botti, B. Ene-Iordache, A. Remuzzi, and D.A.Steinman,"Animage-basedmodelingframeworkforpatient-specific computational hemodynamics," Med. Biol. Eng. Comput., vol. 46, pp. 1097-1112, 2008.