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.
%0 Journal Article
%1 IJACSA.2013.040720
%A Enny Itje Sela Sri Hartati, Agus Harjoko Retantyo Wardoyo Munakhir M S
%D 2013
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K X-Ray; dental osteoporosis; periapical porous segmentation. trabeculae;
%N 7
%T Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening
%U http://ijacsa.thesai.org/
%V 4
%X 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.
@article{IJACSA.2013.040720,
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.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Enny Itje Sela Sri Hartati}, Agus Harjoko Retantyo Wardoyo Munakhir M S},
biburl = {https://www.bibsonomy.org/bibtex/24bd9f9c0ccb8876e3807f0c24677ad6d/thesaiorg},
interhash = {8eadaaa5655a14c0acec6ff49c64deb2},
intrahash = {4bd9f9c0ccb8876e3807f0c24677ad6d},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {X-Ray; dental osteoporosis; periapical porous segmentation. trabeculae;},
number = 7,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening}},
url = {http://ijacsa.thesai.org/},
volume = 4,
year = 2013
}