NDLI: An automated dental caries detection and scoring system for optical images of tooth occlusal surface

Content Provider	IEEE Xplore Digital Library
Author	Ghaedi, L. Gottlieb, R. Sarrett, D.C. Ismail, A. Belle, A. Najarian, K. Hargraves, R.H.
Copyright Year	2014
Description	Author affiliation: Virginia Commonwealth Univ., Richmond, VA, USA (Ghaedi, L.; Gottlieb, R.; Sarrett, D.C.; Hargraves, R.H.) \|\| Temple Univ., Philadelphia, PA, USA (Ismail, A.) \|\| Univ. of Michigan, Ann Arbor, MI, USA (Belle, A.; Najarian, K.)
Abstract	Dental caries are one of the most prevalent chronic diseases. The management of dental caries demands detection of carious lesions at early stages. This study aims to design an automated system to detect and score caries lesions based on optical images of the occlusal tooth surface according to the International Caries Detection and Assessment System (ICDAS) guidelines. The system detects the tooth boundaries and irregular regions, and extracts 77 features from each image. These features include statistical measures of color space, grayscale image, as well as Wavelet Transform and Fourier Transform based features. Used in this study were 88 occlusal surface photographs of extracted teeth examined and scored by ICDAS experts. Seven ICDAS codes which show the different stages in caries development were collapsed into three classes: score 0, scores 1 and 2, and scores 3 to 6. The system shows accuracy of 86.3%, specificity of 91.7%, and sensitivity of 83.0% in ten-fold cross validation in classification of the tooth images. While the system needs further improvement and validation using larger datasets, it presents promising potential for clinical diagnostics with high accuracy and minimal cost. This is a notable advantage over existing systems requiring expensive imaging and external hardware.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	1925
Ending Page	1928
File Size	720506
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6943988
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Teeth Feature extraction Dentistry Image color analysis Accuracy Educational institutions Lesions
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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