Spectroscopic Detection of Caries Lesions

annif.suggestionscaries|efficacy|optical properties|change|wavelength|methods|rules|air conditioning|Finland|machine learning|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p273|http://www.yso.fi/onto/yso/p1655|http://www.yso.fi/onto/yso/p25870|http://www.yso.fi/onto/yso/p277|http://www.yso.fi/onto/yso/p702|http://www.yso.fi/onto/yso/p1913|http://www.yso.fi/onto/yso/p12572|http://www.yso.fi/onto/yso/p6628|http://www.yso.fi/onto/yso/p94426|http://www.yso.fi/onto/yso/p21846en
dc.contributor.authorRuohonen, Mika
dc.contributor.authorPalo, Katri
dc.contributor.authorAlander, Jarmo
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2021-03-22T12:22:47Z
dc.date.accessioned2025-06-25T12:56:26Z
dc.date.available2021-03-22T12:22:47Z
dc.date.issued2013
dc.description.abstractBackground. A caries lesion causes changes in the optical properties of the affected tissue. Currently a caries lesion can be detected only at a relatively late stage of development. Caries diagnosis also suffers from high interobserver variance. Methods. This is a pilot study to test the suitability of an optical diffuse reflectance spectroscopy for caries diagnosis. Reflectance visible/near-infrared spectroscopy (VIS/NIRS) was used to measure caries lesions and healthy enamel on extracted human teeth. The results were analysed with a computational algorithm in order to find a rule-based classification method to detect caries lesions. Results. The classification indicated that the measured points of enamel could be assigned to one of three classes: healthy enamel, a caries lesion, and stained healthy enamel. The features that enabled this were consistent with theory. Conclusions. It seems that spectroscopic measurements can help to reduce false positives at in vitro setting. However, further research is required to evaluate the strength of the evidence for the method’s performance.-
dc.description.notificationCopyright © 2013 Mika Ruohonen et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent9-
dc.format.pagerange1-9-
dc.identifier.olddbid13834
dc.identifier.oldhandle10024/12290
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/1190
dc.identifier.urnURN:NBN:fi-fe202103227989-
dc.language.isoeng-
dc.publisherHindawi Publishing Corporation-
dc.relation.doi10.1155/2013/161090-
dc.relation.ispartofjournalJournal of Medical Engineering-
dc.relation.issn2314-5137-
dc.relation.issn2314-5129-
dc.relation.urlhttps://doi.org/10.1155/2013/161090-
dc.relation.volume2013-
dc.rightsCC BY 4.0-
dc.source.identifierPMID: 27006907-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/12290
dc.subject.disciplinefi=Automaatiotekniikka|en=Automation Technology|-
dc.titleSpectroscopic Detection of Caries Lesions-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|en=A1 Peer-reviewed original journal article|sv=A1 Originalartikel i en vetenskaplig tidskrift|-
dc.type.publicationarticle-
dc.type.versionpublishedVersion-

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