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DOI: 10.14569/IJACSA.2013.040720
PDF

Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening

Author 1: Enny Itje Sela
Author 2: Sri Hartati
Author 3: Agus Harjoko
Author 4: Retantyo Wardoyo
Author 5: Munakhir MS

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 7, 2013.

  • Abstract and Keywords
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Abstract: Segmentation on the trabecular of dental periapical X-Ray images is very important for osteoporosis screening. Existing methods do not perform well in segmenting the trabecular of dental periapical in X-Ray images due to the presence of large amount of spurious edges. This paper presents a combination of tophat-bothat filtering, histogram equalization contrasting and local adaptive thresholding approach for automatic segmentation of dental periapical in X-Ray images. The qualitative evaluation is done by a dentist and shows that the proposed segmentation algorithm performed well the porous of trabecular features of dental periapical. The quantitative evaluation used fuzzy classification based on neural network to classify these features. It were found accuracy rate to be 99,96% for training set and around 65% for testing set for a dataset of 60 subjects.

Keywords: dental periapical X-Ray; osteoporosis; porous trabeculae; segmentation.

Enny Itje Sela, Sri Hartati, Agus Harjoko, Retantyo Wardoyo and Munakhir MS, “Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening ” International Journal of Advanced Computer Science and Applications(IJACSA), 4(7), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040720

@article{Sela2013,
title = {Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040720},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040720},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {7},
author = {Enny Itje Sela and Sri Hartati and Agus Harjoko and Retantyo Wardoyo and Munakhir MS}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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