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A histogram-based algorithm for semiautomated three-dimensional craniofacial modeling
1Department of Radiology, University of Michigan Hospitals, Ann Arbor 48109-0030, USA.
Rationale And Objectives:
I conducted a study designed to facilitate thresholding and reduce volume averaging in three-dimensional (3D) computed tomography (CT) craniofacial modeling.
Methods:
Three-dimensional CT reconstructions of orbits from two cadavers and seven clinical cases were generated from paired axial and coronal data. A histogram-based algorithm that was based on preliminary phantom and craniofacial specimen trials was applied to orbital data to identify volume averaged regions of thin bone to be used in conjunction with standard bone thresholds. Region-of-interest measurement of the orbital floors on the original two-dimensional slice data assessed algorithm performance.
Results:
In five of the nine cases (55%), configuration of the superimposed histograms predicted regions of volume averaging. In only one case did such a region localize to the orbital floor. In the remaining four cases, the air-mucosa interface deep to the orbital floor was identified by the histogram method.
Conclusion:
Operator-dependent editing remains superior to this histogram-based algorithm in reducing volume averaging in 3D craniofacial modeling.
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