2022
DOI: 10.3390/jpm12121954
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Texture-Based Neural Network Model for Biometric Dental Applications

Abstract: Background: The aim is to classify dentition using a novel texture-based automated convolutional neural network (CNN) for forensic and prosthetic applications. Methods: Natural human teeth (n = 600) were classified, cleaned, and inspected for exclusion criteria. The teeth were scanned with an intraoral scanner and identified using a texture-based CNN in three steps. First, through preprocessing, teeth images were segmented by extracting the front-facing region of the teeth. Then, texture features were extracte… Show more

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Cited by 4 publications
(2 citation statements)
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“…The performance of the DL-based model can also be enhanced by applying data treatment/pre-processing steps, as reported in earlier studies, in many applications, such as for human activity recognition [21], breast cancer classification [22], and dental biometrics [23]. Therefore, in this study, we suggested that applying data preprocessing will help in improving the performance of glaucoma detection/classification.…”
Section: Introductionmentioning
confidence: 66%
“…The performance of the DL-based model can also be enhanced by applying data treatment/pre-processing steps, as reported in earlier studies, in many applications, such as for human activity recognition [21], breast cancer classification [22], and dental biometrics [23]. Therefore, in this study, we suggested that applying data preprocessing will help in improving the performance of glaucoma detection/classification.…”
Section: Introductionmentioning
confidence: 66%
“…Beyond 2-dimensional data, including X-rays and photos, facial and intraoral scans can provide highprecision 3-dimensional data for doctors. In Omnia's [38] research, the intraoral scanners they employed could capture tooth details of less than 10 microns. Utilizing unique texture features such as contours, dimensions, bite marks, and more, the automated convolutional neural network can aid in biometric identification for forensic and prosthetic applications.…”
Section: Intraoral Scansmentioning
confidence: 99%