Accuracy assessment of different CBCT acquisition protocols used in rapid prototyping models

Authors

DOI:

https://doi.org/10.33448/rsd-v9i11.9842

Keywords:

Rapid prototyping; Cone beam computed tomograph; Voxel size; Soft tissue simulation.

Abstract

This study compared the acquisition protocols of the Conical Beam Computed Tomography (CBCT) system, to assess the influence on image accuracy by different voxel sizes and the presence of soft tissue. Tomographic acquisition was performed in a fresh (F) and dry (D) pork jaw with voxel sizes of 0.4, 0.3 and 0.25 mm. The gold standard was obtained by scanning dry jaws covered with barium sulfate with a voxel size of 0.25 mm. The images were treated in the MIMICS® program, and noise areas were removed manually, using a fixed threshold for the purpose of generating 3D printing windows. Each window was virtually overlaid with the gold standard using the MeshLab software, obtaining absolute error values ​​between the meshes, generating a map of discrepancies. Significant differences were found between windows D 0.30 vs. F 0.30, D 0.30 vs. F 0.25, D 0.30 vs. D 0.25, D 0.30 vs. F 0.40, F 0.30 vs. D 0.25, F 0.25 vs. D 0.25, F 0.25 vs. D 0.40, D 0.25 vs. F 0.40, D 0.25 vs. D 0.40 and F 0.40 vs. D 0.40, (p <0.05). It was observed that the dry jaw windows showed a lower mean and standard deviation when compared to the fresh jaw windows. The 0.25 mm voxel protocol showed the most accurate result and the presence of soft tissues influenced the accuracy of the image when some protocols were compared statistically.

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Published

13/11/2020

How to Cite

CORAZZA, P. F. L. .; BAEDER, F. M. .; SILVA, D. F.; ALBUQUERQUE, A. C. L. de; SILVA, J. V. L. .; JUNQUEIRA, J. L. C.; PANZARELLA, F. K. Accuracy assessment of different CBCT acquisition protocols used in rapid prototyping models. Research, Society and Development, [S. l.], v. 9, n. 11, p. e2649119842, 2020. DOI: 10.33448/rsd-v9i11.9842. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/9842. Acesso em: 23 apr. 2024.

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Section

Health Sciences