Evidence map›Paper›PMID 35162003›Full record

ArticleSensors (Basel, Switzerland)2022

Cone-Beam Angle Dependency of 3D Models Computed from Cone-Beam CT Images.

Myung Hye Cho, Mohamed A A Hegazy, Min Hyoung Cho, Soo Yeol Lee

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Myung Hye ChoR&D Center, Ray, Seongnam-si 13494, Korea.ORCID 0000-0002-8449-7282
Mohamed A A HegazyR&D Center, Ray, Seongnam-si 13494, Korea.ORCID 0000-0001-7192-2641
Min Hyoung ChoDepartment of Biomedical Engineering, Kyung Hee University, Yongin-si 17104, Korea.
Soo Yeol LeeDepartment of Biomedical Engineering, Kyung Hee University, Yongin-si 17104, Korea.ORCID 0000-0001-7573-2079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cone-beam dental CT can provide high-precision 3D images of the teeth and surrounding bones. From the 3D CT images, 3D models, also called digital impressions, can be computed for CAD/CAM-based fabrication of dental restorations or orthodontic devices. However, the cone-beam angle-dependent artifacts, mostly caused by the incompleteness of the projection data acquired in the circular cone-beam scan geometry, can induce significant errors in the 3D models. Using a micro-CT, we acquired CT projection data of plaster cast models at several different cone-beam angles, and we investigated the dependency of the model errors on the cone-beam angle in comparison with the reference models obtained from the optical scanning of the plaster models. For the 3D CT image reconstruction, we used the conventional Feldkamp algorithm and the combined half-scan image reconstruction algorithm to investigate the dependency of the model errors on the image reconstruction algorithm. We analyzed the mean of positive deviations and the mean of negative deviations of the surface points on the CT-image-derived 3D models from the reference model, and we compared them between the two image reconstruction algorithms. It has been found that the model error increases as the cone-beam angle increases in both algorithms. However, the model errors are smaller in the combined half-scan image reconstruction when the cone-beam angle is as large as 10 degrees.

Indexed as

ArtifactsCone-Beam Computed TomographyAlgorithmsImage Processing, Computer-AssistedImaging, Three-DimensionalPhantoms, Imagingcone-beam artifactcone-beam dental CTdigital impressionhalf-scan image reconstructionstereolithography

Identifiers

PMID35162003
PMCPMC8837983

What OpenQuestion holds

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Registered trials

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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.