Absorption Spectroscopy in Dental Tissue Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F23%3A10464421" target="_blank" >RIV/00216208:11110/23:10464421 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/23:00371373 RIV/60461373:22340/23:43927698

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hU8X9x34xk" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=hU8X9x34xk</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2023.3246299" target="_blank" >10.1109/ACCESS.2023.3246299</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Absorption Spectroscopy in Dental Tissue Analysis

Popis výsledku v původním jazyce

Oral health problems are closely associated with the analysis of dental tissue changes and the stomatologic treatment that follows. This paper explores the use of diffuse reflectance spectroscopy in the detection of dental tissue disorders. The data set includes 343 measurements of teeth spectra in the wavelength range from 400 to 1700 nm. The proposed methodology focuses on computational and statistical methods and the use of these methods for the classification of dental tissue into two classes (healthy and unhealthy) by estimating the probability of class membership. Signal processing is based on the difference between the healthy and unhealthy teeth reflectance spectra in the infrared and visible ranges. Selected features associated with observed spectra are then used for machine learning classification based on the experience of an expert in stomatology during the learning stage. The proposed modification of the weighted k-nearest neighbour method provides class boundaries and the probability of class membership during the verification stage. The accuracy of the classification process reached 95.4%. The proposed methodology and graphical user interface point to the possibility of using absorption spectroscopy in the evaluation of tissue quality changes and its possible implementation in the clinical environment.

Název v anglickém jazyce

Absorption Spectroscopy in Dental Tissue Analysis

Popis výsledku anglicky

Oral health problems are closely associated with the analysis of dental tissue changes and the stomatologic treatment that follows. This paper explores the use of diffuse reflectance spectroscopy in the detection of dental tissue disorders. The data set includes 343 measurements of teeth spectra in the wavelength range from 400 to 1700 nm. The proposed methodology focuses on computational and statistical methods and the use of these methods for the classification of dental tissue into two classes (healthy and unhealthy) by estimating the probability of class membership. Signal processing is based on the difference between the healthy and unhealthy teeth reflectance spectra in the infrared and visible ranges. Selected features associated with observed spectra are then used for machine learning classification based on the experience of an expert in stomatology during the learning stage. The proposed modification of the weighted k-nearest neighbour method provides class boundaries and the probability of class membership during the verification stage. The accuracy of the classification process reached 95.4%. The proposed methodology and graphical user interface point to the possibility of using absorption spectroscopy in the evaluation of tissue quality changes and its possible implementation in the clinical environment.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30208 - Dentistry, oral surgery and medicine

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Svazek periodika

11

Číslo periodika v rámci svazku

February

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

7

Strana od-do

17569-17575

Kód UT WoS článku

000945189400001

EID výsledku v databázi Scopus

2-s2.0-85149176065