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Enregistrement W4242202161 · doi:10.21611/qirt.2010.134

Thermophotonic lock-in imaging: An active thermography system for detecting early carious lesions in human teeth

2010· article· en· W4242202161 sur OpenAlexaff
N. Tabatabaei, A. Mandelis, B.T. Amaechi

Notice bibliographique

RevueProceedings of the 2010 International Conference on Quantitative InfraRed Thermography · 2010
Typearticle
Langueen
DomaineMedicine
ThématiqueInfrared Thermography in Medicine
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésThermographyLock (firearm)DentistryComputer scienceBiomedical engineeringMaterials scienceOpticsMedicineEngineeringInfraredPhysicsMechanical engineering

Résumé

récupéré en direct d'OpenAlex

Lock-in thermography is an active thermographic method that incorporates quadrature demodulation to retrieve the amplitude and phase of the thermal waves generated inside the sample either optically, acoustically or mechanically.The role of subsurface defects, in this case, is then to shift the thermal-wave centroid and therefore produce dynamic contrast, both in amplitude and phase images, with respect to the intact areas.Thanks to recent advances in infrared camera technology, lock-in thermography has been successfully applied to various industrial fields as a powerful non-destructive evaluation technique but less work has been carried out in medical applications of this technology.The case of biological samples is challenging as these samples are usually translucent and do not effectively absorb the applied optical excitation.Even if they do, the medical codes prevent researchers from applying high power excitation to these samples.As a result, the photothermal signals obtained from biological samples are generally poor in terms of signal-to-noise ratio and this makes signal enhancement methods an inevitable part of lock-in thermography systems used in the medical field.The other significant difference of biological samples is that due to their translucency the infrared radiation emanating from them is governed by a coupled diffuse-photon-density and thermal-wave field, as opposed to purely thermal-wave field in opaque samples, which makes the interpretation of the results even more complicated.Mandelis et al. [1] were the first to apply photothermal science to detect early carious lesions in human tooth.There are many benefits in detecting carious lesions in their early stages of progression.These include: 1) increased potential to remineralize the demineralized, noncavitated tooth surfaces; 2) decreased risk of progression to the cavitated stage; 3) reduced probability of tooth sensitivity associated with deeper lesions; 4) maintenance of the natural occlusion; 5) preservation of the natural esthetic appearance of tooth enamel; 6) reduced treatment cost associated with premature and unnecessary surgical interventions.However, these benefits will only be realized if dentists can find a diagnostic method that can effectively detect the carious lesions in their early stages of progression.An X-ray radiograph has poor sensitivity and therefore is incapable of detecting early carious lesions.So far, the most powerful inspection method is visual inspection which depends strongly on the visual capability and experience of the dentist.The experimental results of our research team [1] show that photothermal radiometry is a reliable and sensitive tool in detecting tooth decay in its early stages of progression and this paper is basically an imaging extension of our laser photothermal radiometry using an infrared camera.When light enters the tooth it scatters specially at the carious areas where the pore volume is larger [2].In general, more light scattering in a location results in higher probability of optical absorption, thermal conversion and Planck radiation emission (thermophotonics).As a result, the thermal waves that are generated in porous regions will have greater amplitude than those generated at intact enamel [2].Moreover, as the carious porous areas are close to the surface they shift the thermal-wave centroid closer to the front surface and therefore decrease the phase lag between the applied optical excitation and the surface temperature oscillation.In both cases (amplitude and phase), a pronounced contrast can be observed between intact and carious locations.To verify the capabilities of our thermophotonic lock-in imaging system in detecting early carious lesions in dental samples, extracted human (molars or wisdom) teeth with healthy surfaces were selected.In order to apply controlled demineralization on the tooth samples, a demineralizing solution was prepared.Since our goal was to study the contrast between demineralized and healthy spots in a whole tooth, the tooth was covered with two coats of transparent nail polish except for a rectangular window of size 1mm (W) x 4mm (H), referred to as the treatment window.The demineralization on the window was carried out by submerging the sample upside down in a polypropylene test tube containing 30 ml of demineralizing solution.After the treatment period the sample was removed from the gel, rinsed under running tap water and dried in air.Then, the nail polish was removed from the interrogated surface using acetone and the sample was again rinsed and dried before running thermophotonic lock-in imaging on the sample.After each measurement, the sample was covered again with the transparent nail polish (except for the treatment window) and demineralized for additional days in order to investigate the progression of caries with time.Our infrared camera (CEDIP Titanium 520M, maximum frame rate at full window = 160 Hz) captured the infrared radiation (3.6-5.1 μm) emanating from the sample while it was illuminated by a 808 nm laser with a beam size of 25 mm.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,323
Écart entre enseignants0,289 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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Même revueProceedings of the 2010 International Conference on Quantitative InfraRed ThermographyMême sujetInfrared Thermography in MedicineTravaux en français237 207