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BibTex Citation Data :
@article{JOIV13,
author = {Jufriadif Na`am},
title = {Accuracy of Panoramic Dental X-Ray Imaging in Detection of Proximal Caries with Multiple Morpological Gradient (mMG) Method},
journal = {JOIV : International Journal on Informatics Visualization},
volume = {1},
number = {1},
year = {2017},
keywords = {Proximal Caries; Caries; multiple Morphological Gradient (MMG); Panoramic X-Ray; Smoothing and Sharpening the Edges of Objects},
abstract = {Dental caries is tooth decay caused by bacterial infection. This is commonly known as tooth decay. Classification of caries by location consists of; occlusal caries, proximal caries, root caries and caries enamel. Diagnosis of dental caries in general carried out with the help of radiographic images is called Dental X-Ray. Dental X-Ray consists of bitewing, Periapical and Panoramic. Identification of proximal caries using Dental Panoramic X-Ray lowest precision was compared with both other Dental X-Ray. This study aims to perform sharpening and improving the quality of information contained in the image of Panoramic Dental X-Ray to clarify the edges of the objects contained in the image, making it easier to identify and proximal caries severity. The methods and algorithms used are multiple Morphology Gradient (mMG). The results obtained are increased accuracy in identifying proximal caries 47.5%. Based on the severity of it, that level of enamel = 47.37%; dentin rate = 42.1% and the rate of dentin = 1.3%. Accuracy level of accuracy in identifying proximal caries a higher level of email, so that patients with proximal caries early levels can be tackled early handling by the dentist},
issn = {2549-9904}, pages = {5--11}, doi = {10.30630/joiv.1.1.13},
url = {https://joiv.org/index.php/joiv/article/view/13}
}
Refworks Citation Data :
@article{{JOIV}{13}, author = {Na`am, J.}, title = {Accuracy of Panoramic Dental X-Ray Imaging in Detection of Proximal Caries with Multiple Morpological Gradient (mMG) Method}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {1}, number = {1}, year = {2017}, doi = {10.30630/joiv.1.1.13}, url = {} }Refbacks
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JOIV : International Journal on Informatics Visualization
ISSN 2549-9610 (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W : http://joiv.org
E : joiv@pnp.ac.id, hidra@pnp.ac.id, rahmat@pnp.ac.id
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