Dental enamel is formed by rod‐like structures, the enamel prisms. Groups of prisms are packed together in successive horizontal layers of alternating directions, known as Hunter‐Schreger bands (HSBs). HSBs are the major microstructural characteristic of mammalian enamel. The pattern of HSBs can vary among mammalian species and this variability may provide relevant information regarding the species life history and taxon identification. In human HSBs can be used as a biometric‐based parameter for personal identification in automated systems. The analysis of HSBs has been hampered by technical difficulties. The low contrast between light and dark bands and variations in light intensity may hinder the observation of HSBs in digital images. This article describes a simple and efficient computational procedure that greatly enhances the contrast and minimizes the differences in the intensity of illumination in HSBs images. Its use can significantly increase the quality and the number of HSBs that can be recorded in intact teeth.
Brackground: Tooth enamel is the hardest tissue in human organism, formed by prism layers in regularly alternating directions. These prisms form the Hunter-Schreger Bands (HSB) pattern when under side illumination, which is composed of light and dark stripes resembling fingerprints. We have shown in previous works that HSB pattern is highly variable, seems to be unique for each tooth and can be used as a biometric method for human identification. Since this pattern cannot be acquired with sensors, the HSB region in the digital photograph must be identified and correctly segmented from the rest of the tooth and background. Although these areas can be manually removed, this process is not reliable as excluded areas can vary according to the individual`s subjective impression. Therefore, the aim of this work was to develop an algorithm that automatically selects the region of interest (ROI), thus, making the entire biometric process straightforward.
Results: We used two different approaches: a classical image processing method which we called anisotropy-based segmentation (ABS) and a machine learning method known as U-Net, a convolutional neural network. Both approaches were applied to a set of extracted tooth images. U-Net with some post processing outperformed ABS in the segmentation task with an Intersection Over Union (IOU) of 0.837 against 0.766.
Conclusions: Even with a small dataset, U-Net proved to be a potential candidate for fully automated in-mouth application. However, the ABS technique has several parameters which allow a more flexible segmentation with interactive adjustments specific to image properties.
Eutherian dentition has been the focus of a great deal of studies in the areas of evolution, development, and genomics. The development of molar teeth is regulated by an antero-to-posterior cascade mechanism of activators and inhibitors molecules, where the relative sizes of the second (M2) and third (M3) molars are dependent of the inhibitory influence of the first molar (M1). Higher activator/inhibitor ratios will result in higher M2/M1 or M3/M1. Pax9 has been shown to play a key role in tooth development. We have previously shown that a G-quadruplex in the first intron of Pax9 can modulate the splicing efficiency. Using a sliding window approach with we analyzed the association of the folding energy (Mfe) of the Pax9 first intron with the relative molar sizes in 42 mammalian species, representing 9 orders. The Mfe of two regions located in the first intron of Pax9 were shown to be significantly associated with the M2/M1 and M3/M1 areas and mesiodistal lengths. The first region is located at the intron beginning and can fold into a stable G4 structure, whereas the second is downstream the G4 and 265 bp from intron start. Across species, the first intron of Pax9 varied in G-quadruplex structural stability. The correlations were further increased when the Mfe of the two sequences were added. Our results indicate that this region has a role in the evolution of the mammalian dental pattern by influencing the relative size of the molars.
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