Automatic Inferior Vena Cava segmentation in contrast-enhanced CT volumes

2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Volumn , Issue , 2010, Pages 420-423

  Lefevre, Thierry ^a   Mory, Benoit ^a   Ardon, Roberto ^a   Sanchez Castro, Javier ^a   Yezzi, Anthony ^b  

^a PHILIPS HEALTHCARE   (United States)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMICAL CONSTRAINT; ANATOMICAL VARIABILITY; AUTOMATIC METHOD; AUTOMATIC MODE; CLINICAL DIAGNOSIS; CONTRAST-ENHANCED CT; DATA SETS; GENERALIZED CYLINDERS; IMPLICIT REPRESENTATION; INFERIOR VENA CAVA; LOCAL REGION; OPEN PROBLEMS; SURGERY PLANNING; USER INPUT; VOLUMETRY;

DIAGNOSIS; HUMAN COMPUTER INTERACTION; LIVER; MEDICAL IMAGING; RADIOLOGY;

COMPUTERIZED TOMOGRAPHY;

EID: 77955215577     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2010.5490321     Document Type: Conference Paper

References (15)

1. A.Mihalcea et. al., "A new pc based software for semi automatic liver segmentation. clinical study for preoperative tumor localization," InfoRAD 2003, Radiological Society of North America RSNA, 2003.
2. T. Heimann, B. van Ginneken, and Eds. M. Styner, "3D segmentation in the clinic: A grand challenge," MICCAI, 2007.
3. L. Rusko, G. Bekes, G. Nemeth, and M. Fidrich, "Fully automatic liver segmentation for contrast-enhanced CT images," MICCAI, 3D Segmentation in the Clinic: A Grand Challenge, pp. 143-150, 2007.
4. Y.Chi et. al., "A discussion on the evaluation of a new automatic liver volume segmentation method for specified CT image datasets," MICCAI, pp. 167-175, 2007.
5. S.M. Pizer, D. Eberly, B.M. Morse, and D.S. Fritsch, "Zoominvariant vision of figural shape: The mathematics of cores," Computer Vision and Image Understanding, 1996.
6. A.F. Frangi, W.J. Niessen, R.M. Hoogeveen, T. van Walsum, and M.A. Viergever, "Model-based quantification of 3d magnetic resonance angiographic images," IEEE TMI, vol. 18, no. 10, pp. 946-956, 1999.
7. S. Aylward and E. Bullitt, "Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction," IEEE TMI, vol. 21, no. 2, pp. 61-75, 2002.
8. R. Manniesing et. al., "Level set based cerebral vasculature segmentation and diameter quantification in CT angiography," Medical Image Analysis, vol. 10, pp. 200-214, 2006.
9. M. Hernandez and A.F. Frangi, "Non-parametric geodesic active regions: Method and evaluation for cerebral aneurysms segmentation in 3DRA and CTA," Medical Image Analysis, vol. 11, no. 3, pp. 224-241, 2007.
10. H.Li and A. J. Yezzi, "Vessels as 4-d curves: Global minimal 4-d paths to extract 3-d tubular surfaces and centerlines," IEEE TMI, vol. 26, no. 9, pp. 1213-1223, 2007.
11. Julien Mille, Romuald Boné, and Laurent D. Cohen, "Region-based 2d deformable generalized cylinder for narrow structures segmentation," in ECCV (2), 2008, pp. 392-404.
12. Jules Bloomenthal and Ken Shoemake, "Convolution surfaces," Computer Graphics, vol. 25, no. 4, pp. 251-256, July 1991, Proceedings of SIGGRAPH'91.
13. S. Oeltze and B. Preim, "Visualization of vasculature with convolution surfaces: Method, validation and evaluation," IEEE TMI, vol. 24, no. 4, pp. 540-548, Apr. 2005.
14. S. C. Zhu and A. Yuille, "Region competition: Unifying snakes, region growing, and bayes/mdl for multiband image segmentation," IEEE Trans. On PAMI, 1996.
15. B. Mory, R. Ardon, and Thiran J.P., "Variational segmentation using fuzzy region competition and local non-parametric probability density functions," in ICCV, Proceedings, 2007.