Machine Vision and Applications

, Volume 21, Issue 4, pp 449–467

Salient features useful for the accurate segmentation of masticatory muscles from minimum slices subsets of magnetic resonance images

  • H. P. Ng
  • S. H. Ong
  • S. Huang
  • J. Liu
  • K. W. C. Foong
  • P. S. Goh
  • W. L. Nowinski
Original Paper

DOI: 10.1007/s00138-008-0172-9

Cite this article as:
Ng, H.P., Ong, S.H., Huang, S. et al. Machine Vision and Applications (2010) 21: 449. doi:10.1007/s00138-008-0172-9

Abstract

The masticatory muscles play a critical role in the mastication system and directly affect one’s ability to chew and smile. We describe a new approach for obtaining patient-specific human masticatory muscle surface renderings from magnetic resonance images (MRI) of the head. We determine the set of dominant slices, from training data, that together best represent the salient features of the three-dimensional muscle shape. Candidates for the dominant slices are identified by shape- and area-based criteria, and this is followed by fuzzy C-means clustering to determine the slices that are selected. Two-dimensional segmentation is carried out on these dominant slices on the test data, with shape-based interpolation then applied to construct accurate muscle surface renderings. Performance evaluation using a leave-one-out method results in average overlap indices of greater than 90%, indicating that there is consistency between the surface renderings and manual contour tracings provided by an expert radiologist.

Keywords

Masticatory muscles MRI Dominant slices Fuzzy C-means 

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • H. P. Ng
    • 1
  • S. H. Ong
    • 2
    • 3
  • S. Huang
    • 1
  • J. Liu
    • 1
  • K. W. C. Foong
    • 4
    • 5
  • P. S. Goh
    • 6
  • W. L. Nowinski
    • 1
  1. 1.Biomedical Imaging LabAgency for Science Technology and ResearchSingaporeSingapore
  2. 2.Department of Electrical and Computer EngineeringNational University of SingaporeSingaporeSingapore
  3. 3.Division of BioengineeringNational University of SingaporeSingaporeSingapore
  4. 4.Department of Preventive DentistryNational University of SingaporeSingaporeSingapore
  5. 5.NUS Graduate School for Integrative Sciences and EngineeringSingaporeSingapore
  6. 6.Department of Diagnostic RadiologyNational University of SingaporeSingaporeSingapore

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