Automatic detection of tooth cracks in optical coherence tomography images
Journal of Periodontal & Implant Science
;
: 41-50, 2017.
Article
Dans Anglais
| WPRIM
| ID: wpr-160542
ABSTRACT
PURPOSE:
The aims of the present study were to compare the image quality and visibility of tooth cracks between conventional methods and swept-source optical coherence tomography (SS-OCT) and to develop an automatic detection technique for tooth cracks by SS-OCT imaging.METHODS:
We evaluated SS-OCT with a near-infrared wavelength centered at 1,310 nm over a spectral bandwidth of 100 nm at a rate of 50 kHz as a new diagnostic tool for the detection of tooth cracks. The reliability of the SS-OCT images was verified by comparing the crack lines with those detected using conventional methods. After performing preprocessing of the obtained SS-OCT images to emphasize cracks, an algorithm was developed and verified to detect tooth cracks automatically.RESULTS:
The detection capability of SS-OCT was superior or comparable to that of trans-illumination, which did not discriminate among the cracks according to depth. Other conventional methods for the detection of tooth cracks did not sense initial cracks with a width of less than 100 μm. However, SS-OCT detected cracks of all sizes, ranging from craze lines to split teeth, and the crack lines were automatically detected in images using the Hough transform.CONCLUSIONS:
We were able to distinguish structural cracks, craze lines, and split lines in tooth cracks using SS-OCT images, and to automatically detect the position of various cracks in the OCT images. Therefore, the detection capability of SS-OCT images provides a useful diagnostic tool for cracked tooth syndrome.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Dent
/
Fractures dentaires
/
Interprétation d'images assistée par ordinateur
/
Syndrome de la dent fissurée
/
Tomographie par cohérence optique
Type d'étude:
Etude diagnostique
langue:
Anglais
Texte intégral:
Journal of Periodontal & Implant Science
Année:
2017
Type:
Article
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