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A Bayesian hierarchical model for classifying craniofacial malformations from CT imaging.

Authors
  • Ruiz-Correa, S
  • Gatica-Perez, D
  • Lin, H J
  • Shapiro, L G
  • Sze, R W
Type
Published Article
Journal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publication Date
Jan 01, 2008
Volume
2008
Pages
4063–4069
Identifiers
DOI: 10.1109/IEMBS.2008.4650102
PMID: 19163605
Source
Medline
License
Unknown

Abstract

Single-suture craniosynostosis is a condition of the sutures of the infant's skull that causes major craniofacial deformities and is associated with an increased risk of cognitive deficits and learning/language disabilities. In this paper we adapt to classification of synostostic head shapes a Bayesian methodology that overcomes the limitations of our previously published shape representation and classification techniques. We evaluate our approach in a series of large-scale experiments and show performance superior to those of standard approaches such as Fourier descriptors, cranial spectrum, and Euclidian-distance-based analyses.

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