Evidence map›Paper›PMID 37015249›Full record

ArticleDento maxillo facial radiology2023

Cinematic rendering to improve visualization of supplementary and ectopic teeth using CT datasets.

Ines Willershausen, Fabian Necker, Roman Kloeckner, Corinna Lesley Seidel, Friedrich Paulsen, Lina Gölz, Michael Scholz

Abstract read
In one paragraph

Article in Dento maxillo facial radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ines WillershausenDepartment of Orthodontics and Orofacial Orthopedics, Friedrich-Alexander-University Erlangen-Nürnberg, Gluecksstrasse, Erlangen, Germany.
Fabian NeckerIncubator for Medical Mixed Reality at Stanford (IMMERS), Department of Radiology, Stanford School of Medicine, Stanford, United States.
Roman KloecknerInstitute of Interventional Radiology University Hospital of Schleswig-Holstein-Campus Lübeck, Ratzeburger Allee, Lübeck, Germany.
Corinna Lesley SeidelDepartment of Orthodontics and Orofacial Orthopedics, Friedrich-Alexander-University Erlangen-Nürnberg, Gluecksstrasse, Erlangen, Germany.
Friedrich PaulsenInstitute of Functional and Clinical Anatomy Friedrich-Alexander-University Erlangen-Nürnberg, Krankenhausstrasse, Erlangen, Germany.
Lina GölzDepartment of Orthodontics and Orofacial Orthopedics, Friedrich-Alexander-University Erlangen-Nürnberg, Gluecksstrasse, Erlangen, Germany.
Michael ScholzInstitute of Functional and Clinical Anatomy Friedrich-Alexander-University Erlangen-Nürnberg, Krankenhausstrasse, Erlangen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEctopic, impacted, and supplementary teeth are the number one reason for cross-sectional imaging in pediatric dentistry. The accurate post-processing of acquired data sets is crucial to obtain precise, yet also intuitively understandable three-dimensional (3D) models, which facilitate clinical decision-making and improve treatment outcomes. Cinematic rendering (CR) is anovel visualization technique using physically based volume rendering to create photorealistic images from DICOM data. The aim of the present study was to tailor pre-existing CR reconstruction parameters for use in dental imaging with the example of the diagnostic 3D visualization of ectopic, impacted, and supplementary teeth.

methodsCR was employed for the volumetric image visualization of midface CT data sets. Predefined reconstruction parameters were specifically modified to visualize the presented dental pathologies, dentulous jaw, and isolated teeth. The 3D spatial relationship of the teeth, as well as their structural relationship with the antagonizing dentition, could immediately be investigated and highlighted by separate, interactive 3D visualization after segmentation through windowing.

resultsTo the best of our knowledge, CR has not been implemented for the visualization of supplementary and ectopic teeth segmented from the surrounding bone because the software has not yet provided appropriate customized reconstruction parameters for dental imaging. When employing our new, modified reconstruction parameters, its application presents a fast approach to obtain realistic visualizations of both dental and osseous structures.

conclusionsCR enables dentists and oral surgeons to gain an improved 3D understanding of anatomical structures, allowing for more intuitive treatment planning and patient communication.

Indexed as

Imaging, Three-DimensionalTomography, X-Ray ComputedChildHeadHumansSoftware3D visualizationCBCTCTdental anatomydental radiologyvolume rendering

Identifiers

PMID37015249
PMCPMC10170174

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LicenceCC BY
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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.