Segmentation of Trabecular Jaw Bone on Cone Beam CT Datasets

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Abstract

Background:

The term bone quality is often used in a dentomaxillofacial context, for example in implant planning, as bone density and bone structure have been linked to primary implant success.

Purpose:

This research aimed to investigate the performance of adaptive thresholding of trabecular bone in cone beam CT (CBCT) images. The segmentation quality was assessed for different imaging devices and upper and lower jaws.

Materials and Methods:

Four jaws were scanned with eight CBCT scanners and one micro-CT device. Images of the jaws were spatially aligned with the micro-CT images. Two volumes of interest for each jaw were manually delineated. Trabecular bone in the volumes of interest in the micro-CT images was segmented so that the micro-CT images could serve as high-resolution ground truth images. The volumes of interest in the CBCT images were segmented using both global and adaptive thresholding.

Results:

Segmentation was significantly better for the lower jaw than for the upper jaw. Differences in performance between the scanners were significant for both jaws. Adaptive thresholding performed significantly better in segmenting the bone structure out of CBCT images.

Conclusions:

When assessing jaw bone structure, the observer should always choose adaptive thresholding. It remains a challenge to identify the optimal threshold selection for the structural assessment of jaw bone.

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