Program including abstracts as pdf available here

OP 123
Title
SEGMENTATION OF TRAbECuLAR JAW bONE ON CbCT DATASETS
Authors
O. NACKAERTS 1 , M. DEPyPERE 2 , G. zHANG 3 , F. MAES 2 , R. JACObS 1 , SEDENTEXCT 4
Affiliations
1 Oral Imaging Centre, KU Leuven, Leuven, BELGIUM, 2 ESAT, KU Leuven, Leuven, BELGIUM, 3
Radiology, KU Leuven, Leuven, BELGIUM, 4 www.sedentexCT.eu, Manchester, UNITED KINGDOM
Body
Aims
The aim of this research was to assess the accuracy of segmentation procedures on CBCT images
with µCT images as the reference standard.
Method
Four human formalin-fixed jaws including soft tissues were scanned with 9 different CBCT
devices with a µCT device.
In CT-analyser, 2 regions of interest for each jaw were chosen. The regions of interest were
segmented for each CBCT scanner, first with global, then with adaptive thresholding. Finally,
one observer performed the thresholding manually.
The optimal threshold was determined for each scanner with ROC analysis and compared to
manual thresholding. The reference standard for ROC analysis was the (manual) thresholding
on the µCT scans.
Results
Adaptive thresholding yielded much higher accuracy levels than global thresholding. Moreover,
adaptive thresholding was less sensitive to shifts in thresholding. The device classification
based on best accuracy was comparable to intuitive image quality assessment.
With manual thresholding, a consistent underestimation of bone volume occurred. This was
most probably due to the borders of the regions of interest, where more opaque areas are
visible.
Conclusion
Adaptive thresholding is an easy way of rendering bone segmentation on CBCT more stable and
of a higher quality than can be done with global thresholding. With manual thresholding, the
focus should be on the central part of the regions of interest. Follow-up research will aim at
defining a valid way for automatic optimal threshold detection.
Keywords
bone, µCT, segmentation
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