Diffuse reflectance spectroscopy in dental caries detection and classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F20%3A10411843" target="_blank" >RIV/00216208:11110/20:10411843 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/20:00347294 RIV/00179906:_____/20:10411843 RIV/00216208:11150/20:10411843 RIV/60461373:22340/20:43920945
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=MxP6h0glZQ" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=MxP6h0glZQ</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11760-020-01640-4" target="_blank" >10.1007/s11760-020-01640-4</a>

Result language
angličtina
Original language name
Diffuse reflectance spectroscopy in dental caries detection and classification
Original language description
Machine learning and augmented reality form very important computational tools in biomedicine, neurology and stomatology as well. The present paper is devoted to a novel method of spectroscopic detection of caries lesions that changes the optical properties of the affected tissue. This method of the diffuse reflectance spectroscopy is used in many biomedical areas even though the analysis of associated data suffers from a large variance of acquired signals' shape and their properties. The proposed methodology of measured spectra analysis is based upon general methods of signal feature evaluation and the use of computational intelligence for their classification. The paper compares properties of dental feature clusters for the set of 578 tissues with different levels of their changes. Classification results of selected features by the support vector machine, Bayesian method, k-nearest neighbour method and neural network enable to distinguish the healthy tissue and caries lesions with the accuracy from 94.1 to 98.4% and the cross-validation error lower than 8.3%. These results suggest how the augmented reality and general mathematical signal processing methods can be beneficial for diagnostic purposes in dental research and possibly in the clinical practice as well.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
30208 - Dentistry, oral surgery and medicine

Project
<a href="/en/project/EF17_048%2F0007441" target="_blank" >EF17_048/0007441: PERSONMED - Center for the Development of Personalized Medicine in Age-Related Diseases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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