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Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs
- Source :
- Applied Sciences, Volume 11, Issue 13, Applied Sciences, Vol 11, Iss 5850, p 5850 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- The cemento-enamel junction (CEJ) is an important reference point for various clinical measurements in oral health assessment. Identifying CEJ in ultrasound images is a challenging task for dentists. In this study, a computer-assisted detection method is proposed to identify the CEJ in ultrasound images, based on the curvature change of the junction outlining the upper edge of the enamel and cementum at the cementum–enamel intersection. The technique consists of image preprocessing steps for image enhancement, segmentation, and edge detection to locate the boundary of the enamel and cementum. The effects of the image preprocessing and the sizes of the bounding boxes enclosing the CEJ were studied. For validation, the algorithm was applied to 120 images acquired from human volunteers. The mean difference of the best performance between the proposed method and the two raters’ measurements was an average of 0.25 mm with reliability ≥ 0.98. The proposed method has the potential to assist dental professionals in CEJ identification on ultrasonographs to provide better patient care.
- Subjects :
- Technology
QH301-705.5
landmark detection
Computer science
QC1-999
Cemento-enamel junction
Image processing
Oral health
Intersection (Euclidean geometry)
Edge detection
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
stomatognathic system
Preprocessor
General Materials Science
Computer vision
Segmentation
Biology (General)
dento-periodontium
cemento-enamel junction
QD1-999
Instrumentation
Fluid Flow and Transfer Processes
Enamel paint
business.industry
Physics
Process Chemistry and Technology
General Engineering
030206 dentistry
high-frequency ultrasound
Engineering (General). Civil engineering (General)
image processing
3. Good health
Computer Science Applications
Chemistry
stomatognathic diseases
visual_art
visual_art.visual_art_medium
oral health
Artificial intelligence
TA1-2040
business
Subjects
Details
- ISSN :
- 20763417
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Applied Sciences
- Accession number :
- edsair.doi.dedup.....5687bd5d85338e7ee7acfec7bf1caec0