The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images.

Friedli, Luca; Kloukos, Dimitrios; Kanavakis, Georgios; Halazonetis, Demetrios; Gkantidis, Nikolaos (2020). The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images. Scientific reports, 10(1), p. 7361. Springer Nature 10.1038/s41598-020-64383-9

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The use of a single grey intensity threshold is one of the most straightforward and widely used methods to segment cranial base surface models from a 3D radiographic volume. In this study we used thirty Cone Beam Computer Tomography (CBCT) scans from three different machines and ten CT scans of growing individuals to test the effect of thresholding on the subsequently produced anterior cranial base surface models. From each scan, six surface models were generated using a range of voxel intensity thresholds. The models were then superimposed on a manually selected reference surface model, using an iterative closest point algorithm. Multivariate tests showed significant effects of the machine type, threshold value, and superimposition on the spatial position and the form of the created models. For both, CT and CBCT machines, the distance between the models, as well as the variation within each threshold category, was consistently increasing with the magnitude of difference between thresholds. The present findings highlight the importance of accurate anterior cranial base segmentation for reliable assessment of craniofacial morphology through surface superimposition or similar methods that utilize this anatomical structure as reference.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > School of Dental Medicine > Department of Orthodontics

UniBE Contributor:

Friedli, Luca; Kloukos, Dimitrios and Gkantidis, Nikolaos

Subjects:

600 Technology > 610 Medicine & health

ISSN:

2045-2322

Publisher:

Springer Nature

Language:

English

Submitter:

Renate Imhof-Etter

Date Deposited:

11 May 2020 21:04

Last Modified:

17 May 2020 02:46

Publisher DOI:

10.1038/s41598-020-64383-9

PubMed ID:

32355261

BORIS DOI:

10.7892/boris.143917

URI:

https://boris.unibe.ch/id/eprint/143917

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