Evidence map›Paper›PMID 32038865›Full record

ArticleHealthcare technology letters2019

Towards AR-assisted visualisation and guidance for imaging of dental decay.

Yaxuan Zhou, Paul Yoo, Yingru Feng, Aditya Sankar, Alireza Sadr, Eric J Seibel

Open access · goldAbstract read
In one paragraph

Article in Healthcare technology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 7% of its field
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Review
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

6 authors at 1 institution in 1 country.

Yaxuan ZhouDepartment of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-6639-0078
Paul YooPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.
Yingru FengPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.
Aditya SankarPaul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-7937-1482
Alireza SadrSchool of Dentistry, University of Washington, Seattle, WA 98195, USA.
Eric J SeibelHuman Photonics Lab, Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA.
University of Washington · US

Funding

Multispectral near-infrared imaging of dental caries in childrenR21DE025356 · NIDCR · UNIVERSITY OF WASHINGTON · PI SEIBEL, ERIC J · 2016 to 2017
$417k
NIDCR NIH HHS R21 DE025356
6 · The paper itself

Abstract

Untreated dental decay is the most prevalent dental problem in the world, affecting up to 2.4 billion people and leading to a significant economic and social burden. Early detection can greatly mitigate irreversible effects of dental decay, avoiding the need for expensive restorative treatment that forever disrupts the enamel protective layer of teeth. However, two key challenges exist that make early decay management difficult: unreliable detection and lack of quantitative monitoring during treatment. New optically based imaging through the enamel provides the dentist a safe means to detect, locate, and monitor the healing process. This work explores the use of an augmented reality (AR) headset to improve the workflow of early decay therapy and monitoring. The proposed workflow includes two novel AR-enabled features: (i) in situ visualisation of pre-operative optically based dental images and (ii) augmented guidance for repetitive imaging during therapy monitoring. The workflow is designed to minimise distraction, mitigate hand-eye coordination problems, and help guide monitoring of early decay during therapy in both clinical and mobile environments. The results from quantitative evaluations as well as a formative qualitative user study uncover the potentials of the proposed system and indicate that AR can serve as a promising tool in tooth decay management.

Indexed as

augmented guidanceaugmented realitydata visualisationdentistryearly decay management difficultearly decay therapyenamelsexpensive restorative treatmenthelp guide monitoringirreversible effectsmedical image processingmitigate hand–eye coordination problemspatient treatmentpre-operative optically based dental imagesprevalent dental problemquantitative monitoringrepetitive imagingsignificant economic burdensitu visualisationsocial burdentherapy monitoringtooth decay managementunreliable detectionuntreated dental decay

Identifiers

PMID32038865
PMCPMC6952244
OpenAlexW2979816588

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.