Evidence map›Paper›PMID 32882986›Full record

ArticleInternational journal of environmental research and public health2020

Impacts of Thresholds of Gray Value for Cone-Beam Computed Tomography 3D Reconstruction on the Accuracy of Image Matching with Optical Scan.

Se-Won Park, Ra Gyoung Yoon, Hyunwoo Lee, Heon-Jin Lee, Yong-Do Choi, Du-Hyeong Lee

Abstract read
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Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Se-Won ParkDepartment of Prosthodontics, School of Dentistry, Institute for Translational Research in Dentistry, Kyungpook National University, Daegu 41940, Korea.ORCID 0000-0003-2850-0333
Ra Gyoung YoonDepartment of Radiology, Nowon Eulji Medical Center, Eulji University, Seoul 01830, Korea.
Hyunwoo LeeDepartment of Dental Clinic, National Medical Center, Seoul 04564, Korea.
Heon-Jin LeeDepartment of Microbiology and Immunology, School of Dentistry, Kyungpook National University, Daegu 41940, Korea.ORCID 0000-0002-1911-5014
Yong-Do ChoiDepartment of Prosthodontics, School of Dentistry, Institute for Translational Research in Dentistry, Kyungpook National University, Daegu 41940, Korea.
Du-Hyeong LeeDepartment of Prosthodontics, School of Dentistry, Institute for Translational Research in Dentistry, Kyungpook National University, Daegu 41940, Korea.ORCID 0000-0003-2803-7457

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In cone-beam computed tomography (CBCT), the minimum threshold of the gray value of segmentation is set to convert the CBCT images to the 3D mesh reconstruction model. This study aimed to assess the accuracy of image registration of optical scans to 3D CBCT reconstructions created by different thresholds of grey values of segmentation in partial edentulous jaw conditions. CBCT of a dentate jaw was reconstructed to 3D mesh models using three different thresholds of gray value (-500, 500, and 1500), and three partially edentulous models with different numbers of remaining teeth (4, 8, and 12) were made from each 3D reconstruction model. To merge CBCT and optical scan data, optical scan images were registered to respective 3D reconstruction CBCT images using a point-based best-fit algorithm. The accuracy of image registration was assessed by measuring the positional deviation between the matched 3D images. The Kruskal-Wallis test and a post hoc Mann-Whitney U test with Bonferroni correction were used to compare the results between groups (α = 0.05). The correlations between the experimental factors were calculated using the two-way analysis of variance test. The positional deviations were lowest with the threshold of 500, followed by the threshold of 1500, and then -500. A significant interaction was found between the threshold of gray values and the number of remaining teeth on the registration accuracy. The most significant deviation was observed in the arch model with four teeth reconstructed with a gray-value threshold of -500. The threshold for the gray value of CBCT segmentation affects the accuracy of image registration of optical scans to the 3D reconstruction model of CBCT. The appropriate gray value that can visualize the anatomical structure should be set, especially when few teeth remain in the dental arch.

Indexed as

Cone-Beam Computed TomographyImaging, Three-DimensionalToothAlgorithmsHumansImage Processing, Computer-Assisted3D reconstructionaccuracycone-beam computed tomographygray valueimage registration

Identifiers

PMID32882986
PMCPMC7503962

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.