A 3D statistical shape model of the pelvic bone for segmentation

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5370 II, Issue , 2004, Pages 1341-1351

  Lamecker, Hans ^a   Seebaß, Martin ^b   Hege, Hans Christian ^a   Deuflhard, Peter ^a  

^a ZUSE INSTITUTE BERLIN   (Germany)

^b Indeed Visual Concepts GmbH   (Germany)

Author keywords

3d correspondence problem; Model based segmentation; Pelvic bone; Statistical shape models

Indexed keywords

BONE; DATA ACQUISITION; HYPOTHERMIA; IMAGE PROCESSING; MATHEMATICAL MODELS; OPTIMIZATION; ROBUSTNESS (CONTROL SYSTEMS); STATISTICAL METHODS; TUMORS;

3D CORESPONDENSE PROBLEM; MODEL-BASED SEGMENTATION; PELVIC BONE; STATISTICAL SHAPE MODELS;

MEDICAL IMAGING;

EID: 5644227467     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.534145     Document Type: Conference Paper

References (17)

1. Y. Wang, B. S. Peterson, and L. H. Staib, "Shape-based 3D surface correspondence using geodesics and local geometry," in CVPR 2000, 2, pp. 644-651, 2000.
2. A. Kelemen, G. Székely, and G. Gerig, "Three-dimensional model-based segmentation of brain MRI," IEEE Trans. on Medical Imaging 18(10), pp. 828-839, 1999.
3. T. Cootes, A. Hill, C. J. Taylor, and J. Haslam, "Use of active shape models for locating structures in medical images," Image and Vision Computing 12, pp. 355-366, 1994.
4. P. M. Thompson and A. W. Toga, "Detection, visualization and animation of abnormal anatomic structure with a deformable probabilistic brain atlas based on random vector field transformations," Medical Image Analysis 1(4), pp. 271-294, 1996.
5. M. Fleute, S. Lavallee, and R. Julliard, "Incorporating a statistically based shape model into a system for computed-assisted anterior cruciate ligament surgery," Medical Image Analysis 3(3), pp. 209-222, 1999.
6. A. F. Frangi, D. Rückert, J. A. Schnabel, and W. J. Niessen, "Construction of multiple-object three-dimensional statistical shape models: Application to cardiac modelling," IEEE Transactions on Medical Imaging 21(9), pp. 1151-1166, 2002.
7. A. D. Brett and C. J. Taylor, "A method of automated landmark generation for automated 3D PDM construction," Imag. Vis. Comp. 18(9), pp. 739-748, 2000.
8. A. D. Brett and C. J. Taylor, "Automated construction of 3D shape models using harmonic maps," in Medical Image Understanding and Analysis, S. Arridge and A. Todd-Pokropek, eds., pp. 175-178, (London, U.K.), 2000.
9. T. Duchamp, A. Certain, T. DeRose, and W. Stuetzle, "Hierarchical computation of PL harmonic embeddings," tech. rep., University of Washington, July 1997.
10. R. H. Davies, C. Twining, T. Cootes, J. C. Waterton, and C. J. Taylor, "A minimum description length approach to statistal shape modelling," IEEE Transactions on Medical Imaging 21, pp. 525-537, May 2002.
11. H. Lamecker, T. Lange, and M. Seebaß, "A statistical shape model for the liver," in MICCAI 2002, 2489, pp. 422-427, 2002.
12. H. Lamecker, T. Lange, and M. Seebaß, "Segmentation of the liver using a 3d statistical shape model," submitted, 2003.
13. A. D. McLachlan, "Least squares fitting of two structures," J. Mol. Biol. 128, pp. 74-79, 1979.
14. M. S. Floater, "Parameterization and smooth approximation of surface triangulations," Computer Aided Geometric Design 14(3), pp. 231-250, 1997.
15. B. O'NEILL, Elementary differential geometry, Academic press, 1966.
16. M. Zöckler, D. Stalling, and H.-C. Hege, "Fast and intuitive generation of geometric shape transitions," The Visual Computer 16(5), pp. 241-253, 2000.
17. M. Garland and P. S. Heckbert, "Simplification using quadratic error metrices," in SIGGRAPH 97, pp. 209-216, 1997.