Evidence map›Paper›PMID 31356110›Full record

ArticleDento maxillo facial radiology2020

3D-cinematic rendering for dental and maxillofacial imaging.

Bernd Stadlinger, Silvio Valdec, Lorenz Wacht, Harald Essig, Sebastian Winklhofer

Abstract read
In one paragraph

Article in Dento maxillo facial radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Cinematic rendering of [European journal of nuclear medicine and molecular imaging · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Application Value of the CT Scan 3D Reconstruction Technique in Maxillofacial Fracture Patients.Evidence-based complementary and alternative medicine : eCAM · 2022
    Article
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

5 authors.

Bernd StadlingerClinic of Cranio-Maxillofacial and Oral Surgery, University Hospital Zurich, University of Zurich, Switzerland.
Silvio ValdecClinic of Cranio-Maxillofacial and Oral Surgery, University Hospital Zurich, University of Zurich, Switzerland.
Lorenz WachtDepartment of Radiology and Nuclear Medicine, Triemli Hospital Zurich, Switzerland.
Harald EssigClinic of Cranio-Maxillofacial and Oral Surgery, University Hospital Zurich, University of Zurich, Switzerland.
Sebastian WinklhoferDepartment of Neuroradiology, University Hospital Zurich, University of Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAim of this technical note is to show the applicability of cinematic rendering (CR) for a photorealistic 3-dimensional (3D) visualization of maxillofacial structures. The focus is on maxillofacial hard tissue pathologies.

methodsHigh density maxillofacial pathologies were selected in which CR is applicable. Data from both, CT and cone beam CT (CBCT) were postprocessed using a prototype CR software.

resultsCR 3D postprocessing of CT and CBCT imaging data is applicable on high density structures and pathologies such as bones, teeth, and tissue calcifications. Image reconstruction allows for a detailed visualization of surface structures, their plasticity, and 3D configuration.

conclusionsCR allows for the generation of photorealistic 3D reconstructions of high density structures and pathologies. Potential applications for maxillofacial bone and tooth imaging are given and examples for CT and CBCT images are displayed.

Indexed as

Imaging, Three-DimensionalToothCone-Beam Computed TomographyHumansImage Processing, Computer-AssistedMaxillaSoftwarecone-beam CTimagingmaxillofacial abnormalitiesmultidetector CTthree-dimensional

Identifiers

PMID31356110
PMCPMC6957071

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.