Symbolic shape descriptors for classifying craniosynostosis deformations from skull imaging

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 7 VOLS, Issue , 2005, Pages 6325-6331

  Lin, H J ^a   Ruiz Correa, S ^b,f   Shapiro, L G ^d   Hing, A V ^c,f   Cunningham, M L ^c,f   Speltz, M L ^e   Sze, R W ^b,f  

^a Department of Biomedical and Health Informatics ^*

^b Faculty of Radiology

^c Faculty of Pediatrics

^d Faculty of Computer Science and Engineering

^e UNIVERSITY OF WASHINGTON   (United States)

^f SEATTLE CHILDREN S RESEARCH INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CARDIOLOGY; CLASSIFICATION (OF INFORMATION); FOURIER TRANSFORMS; MATHEMATICAL MODELS; MEDICAL IMAGING; PULMONARY DISEASES;

CRANIOSYNOSTOSIS DEFORMATIONS; NUMERIC DESCRIPTORS; SKULL IMAGING; SYMBOLIC SHAPE DESCRIPTORS;

BIOLOGICAL ORGANS;

EID: 33846927565     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iembs.2005.1615944     Document Type: Conference Paper

References (27)

1. H. Chui, A. Rangarajan, J. Zhang, and C. M. Leonard. Unsupervised learning of an atlas from unlabeled point-sets. IEEE Trans. Pattern Anal. Mach. Intell., 26(2): 160-172, 2004.
2. A.P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelyhood from incomplete data via the em algorithm. J. Royal Statist, Soc. B, 39, pages =, 1977.
3. I. Dryden and K. Mardi. Sratistical Shape Analysis. NewYork:Wiley, 1998.
4. B. Efron. The Jackknife, the Bootstrap, and Other Resampling Plans. Society for Industrial and Applied Mathematics, 1982.
5. J. J. Fata and M. S. Turner. The reversal exchange technique of total calvarial reconstruction for sagittal synostosis. Plast Reconst Surg, 107(7): 1637-1646, 2001.
6. P. Golland. Discriminative direction for kernel classifiers. In Advances in Neural Information Processing Systems, volume 13, pages 745-752, 2001.
7. J. Guimaras-Ferreira, F. Gewalli, L. David, R. Olsson, H. Freide, and C.G.K. Lauritzen. Spring-mediated cranioplasty compared with the modified pi-plasty for sagittal synostosis. Scand J Plast Surg Hand Surg, 37:209-215, 2003.
8. R. M. Haralick and L. G. Shapiro. Compurer and Robot Vision. Addison-Wesley, 1992.
9. T. Hofmann. Unsupervised learning by Probabulistic Latent Semantic Analysis. Machine Learning, 42:177-196, 2001.
10. D. F. Jimenez, C. M. Barone, M. E. McGee, and C. C. Cartwrightand C. L. Baker. Endoscopy-assisted wide vertex craniectomy, barrel stave osteotomies, and postoperative molding therapy in management of sagittal suture synostosis. Journal Neurosurg (pediatrics 5), 100:407-417, 2004.
11. E. Lajeunie, M. Le Merrer, C. Marchac, and D. Renier. Genetic study of scaphocepaly. Am J med Genet, (62):282-285, 1996.
12. S. R. Lale and J. T. Richtsmeier. An Invariant approach to statistical analysis of shape. Chapman and Hall/CRC, 2001.
13. M. Lynch and B. Walsh. Genetics and Analysis of quantitative trait. Sinauer Associates, 1998.
14. J. Martin, A. Pentland, S. Sclaroff, and R. Kikinis. Characterization of neurophatological shape deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2(2), 1998.
15. J. Panchal, J.L. Marsh, T.S. Park, B. Hauffman, T. Pilgram, and S.H. Huang. Sagittal craniosynostosis outcome assessment for two methods of timings and interventions. Plast Reconstr Surg, 103(6): 1574-1579, 1999.
16. C. Rao. Geometry of circular vectors and pattern recognition of shape of a boundary. Proc. Nat. Acad. Sci., 95:12783, 2002.
17. M. Rogers and J. Graham. Robust active shape model search. In 7th European Conference on Computer Vision 2002, volume 4, pages 517-530.
18. S. Ruiz-Correa, L. G. Shapiro, and M. Meilǎ. A new paradigm for recognizing 3-d object shapes from range data. In IEEE International Conference on Computer Vision, volume 2, pages 1126-1133, 2003.
19. S. Ruiz-Correa, L. G. Shapiro, M. Meilǎ, and G. Berson. Discriminating deformable shape classes. In Sebastian Thrun, Lawrence Saul, and Bernhard Schölkopf, editors, Advances in Neural Information Processing Systems 16. MIT Press, Cambridge, MA, 2004.
20. S. Ruiz-Correa, L. G. Shapiro, M. Meilǎ, G. Berson, M. L. Cunningham, and R. W. Sze. Symbolic signatures for deformable shapes. In press, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005.
21. S. Ruiz-Correa, R. W. Sze, H. J. Lin, L. G. Shapiro, M. L. Speltz, and M. L. Cunningham. Classifying craniosynostosis deformations by skull shape imaging. Proceedings of the IEEE Conference on Computer-Based Medical Systems, 2005. In press.
22. S. Ruiz-Correa, R. W. Sze, J. R. Starr, A. V. Hing, H. J. Lin, and M. L. Cunningham. A Fourier-based approach for quantifying sagittal synostosis head shape. American Cleft Palate-Craniofacial Association Meeting, 2005.
23. S. Ruiz-Correa, R. W. Sze, J. R. Starr, H. J. Lin, M. L. Speltz, M. L. Cunningham, and A. V. Hing. New scaphocephaly severity indices of sagittal craniosynostosis: A comparative study with cranial index quantifications. Submitted to the American Cleft Palate-Craniofacial Association Journal, 2005.
24. G. Salton and M. J. McGill. Introduction to Modern Information Retrieval. New York: McGraw-Hill, 1983.
25. B. Scholköpf and A. J. Smola. Learning with Kernels. Cambridge University Press, 2002.
26. K. Seymour-Dempsey, J. E. Bautngartner, J. F. Teichgraeber, J. J. Xia, A. L. Waller, and J. Gaetano. Molding helmet therapy in the management of sagittal synostosis. The Journal of Craniofacial Surgery, 13(5):631-635, 2002.
27. V. V. Vapnik. Statistical Learning Theory. John Wiley and Sons, 1998.