Thermophotonic lock-in imaging: An active thermography system for detecting early carious lesions in human teeth
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".