Multi-modal imaging of tooth microcrack

Irma Dumbryte; Donatas Narbutis; Maria Androulidaki; Elena Jasiuniene; Arturas Vailionis; Saulius Juodkazis; Mangirdas Malinauskas

doi:10.1117/12.2692782

13 March 2024 Multi-modal imaging of tooth microcrack

Irma Dumbryte, Donatas Narbutis, Maria Androulidaki, Elena Jasiuniene, Arturas Vailionis, Saulius Juodkazis, Mangirdas Malinauskas

Author Affiliations +

Proceedings Volume 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences; 128570A (2024) https://doi.org/10.1117/12.2692782
Event: SPIE BiOS, 2024, San Francisco, California, United States

Conference Poster

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Irma Dumbryte, Donatas Narbutis, Maria Androulidaki, Elena Jasiuniene, Arturas Vailionis, Saulius Juodkazis, and Mangirdas Malinauskas "Multi-modal imaging of tooth microcrack", Proc. SPIE 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, 128570A (13 March 2024); https://doi.org/10.1117/12.2692782

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