The aim of the study was to combine an X-ray micro-computed tomography (μCT), enhanced with convolutional neural network (CNN) assisted voxel classification and volume segmentation, with photoluminescence (PL) and micro-Raman spectroscopy (μ-RS) for tooth structural integrity evaluation at the microcrack (MC) site of the extracted human teeth. Four maxillary premolars with visible enamel MCs were first examined utilizing an X-ray μCT and segmented with CNN to identify enamel, dentin, and cracks. Secondly, buccal and palatal teeth surfaces with MCs and sound areas were used to obtain fluorescence spectra illuminated with laser exposure wavelengths of 325 nm (CW) and 266 nm (0.5 ns pulsed), spot diameter ~ 80 μm. Thirdly, chemical composition inside the crack and the difference from the sound area were determined utilizing μ-RS method with a 785 nm laser (CW), spot diameter ∼ 3 μm. The proposed approach, which sequentially integrates X-ray μCT in combination with CNN assisted segmentation, PL, and μ-RS, revealed variations in the material composition along the crack line compared to the sound enamel. This includes alterations in the hydroxyapatite crystals’ quantity and/or quality at the sites of cracks versus uncracked enamel, suggesting a potential compromise in the structural integrity of the tooth in the areas affected by MCs.
The study aimed to combine an X-ray micro-computed tomography (μCT) with photoluminescence (PL) and convolutional neural network (CNN) assisted voxel classification and volume segmentation for tooth structural integrity assessment at the microcrack site and verify this approach with extracted human teeth. The samples were first examined using an X-ray μCT and segmented with CNN to identify enamel, dentin, and cracks. A new CNN image segmentation model was trained based on “Multiclass semantic segmentation using DeepLabV3+” example and was implemented with “TensorFlow”. Secondly, buccal and palatal teeth surfaces with microcracks and sound areas were selected to obtain fluorescence spectra illuminated with wavelengths of 325 nm (cw) and 266 nm (0.5 ns pulsed). The proposed approach – using X-ray μCT in combination with PL and CNN assisted segmentation – reveals the possibilities for tooth structural integrity assessment at the crack area with distinct precision and versatility and can be applied for all the teeth microstructure and surface mapping analysis.
Laser 3D nanolithography as an additive manufacturing technology allows the fabrication of various objects at a micro-scale, with possible nano-scale single features. An absorption mechanism plays the key role, thus polymerization reaction starts only at a certain value of light intensity I, which also alters because of possible different non-linearities of light-matter interaction when different wavelengths are used. Both polymerization and optical damage thresholds and the feature size depend on the applied I and energy dose E. In this work, the experiment was performed within the 700-1250 nm wavelength range while varying pulse duration (~ 100-300 fs). We present how the polymerization process (thresholds and feature sizes) depends on both wavelength and pulse duration in the SZ2080TM prepolymer.
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