Detection of carious lesion by laser speckle analysis using the first order moment
DOI:
https://doi.org/10.33448/rsd-v9i12.11039Keywords:
Laser speckle imaging; Diagnostic; Computer vision; Dental Caries.Abstract
Carious lesion is one of the most prevalent diseases in humankind, affecting nearly all human beings at least once in a lifetime. Early carious lesion (ECL, also known as white spot lesion) is part of the caries process in which the enamel surface loses mineral but the subsurface layer overlying the mineral-poor region remains intact. In its early stages, the detection of the carious lesion is currently still a major challenge because it is based on visual inspection, thus with an inherent subjectivity. In this work, we present a method to detect and assess the severity of ECLs using a computer-assisted laser speckle imaging technique. Forty-five polished and cut bovine incisors samples allow a paired t-test by exposing half of the surface while protecting the other half. The samples, included in a PVC tube, were immersed in 50ml of a solution (pH 5.0) containing 0.05M acetate buffer solution and 50% saturated hydroxyapatite enamel powder at 37°C. The etching time is 24h; 48h and 72h; each group contain 15 samples. We illuminate each sample with a laser and analyse the first momentum of the laser speckle images with a computer. Our results shows that the first momentum of the LSI of the sound region statistically differs from the decay region of the samples for all groups (p<0.0001). We also found a strong correlation between the acid etch duration (severity of the decay) and the shift in LSI contrast (Pearson’s correlation coefficient ρ=0.9989, R²=0.9978). Detecting decay in its early stages is still a challenge in the clinical practice, however this work demonstrates that the analysis of the statistical features of the laser speckle image in the spatial domain allows for the detection of microstructural changes in the enamel associated with the presence of the lesion even before any intervention is required.
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Copyright (c) 2020 João Vagner Pereira da Silva; Ravana Angelini Sfalcin; Vola Masoandro Andrianarijaona; Luciano Gillieron Gavinho; Luciana Toledo Costa Salviatto; Sandra Kalil Bussadori; Alessandro Melo Deana
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