Binary Mask Pattern Segmentation in glaucoma detection
M. Arulmary1 , S.P. Victor2
Section:Research Paper, Product Type: Journal Paper
Volume-6 ,
Issue-9 , Page no. 255-259, Sep-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i9.255259
Online published on Sep 30, 2018
Copyright © M. Arulmary, S.P. Victor . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: M. Arulmary, S.P. Victor, “Binary Mask Pattern Segmentation in glaucoma detection,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.255-259, 2018.
MLA Style Citation: M. Arulmary, S.P. Victor "Binary Mask Pattern Segmentation in glaucoma detection." International Journal of Computer Sciences and Engineering 6.9 (2018): 255-259.
APA Style Citation: M. Arulmary, S.P. Victor, (2018). Binary Mask Pattern Segmentation in glaucoma detection. International Journal of Computer Sciences and Engineering, 6(9), 255-259.
BibTex Style Citation:
@article{Arulmary_2018,
author = {M. Arulmary, S.P. Victor},
title = {Binary Mask Pattern Segmentation in glaucoma detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {255-259},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2854},
doi = {https://doi.org/10.26438/ijcse/v6i9.255259}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.255259}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2854
TI - Binary Mask Pattern Segmentation in glaucoma detection
T2 - International Journal of Computer Sciences and Engineering
AU - M. Arulmary, S.P. Victor
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 255-259
IS - 9
VL - 6
SN - 2347-2693
ER -
VIEWS | XML | |
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Abstract
Glaucoma detection is one of the most recent researches in medical field. There are several researches which mainly focus on optic cup to disc ratio to efficiently identify glaucoma. The objective of this paper is to identify glaucoma by creating a binary mask for optic cup and disc of glaucomatous eyes. The query image is segmented using these masks and identified as either normal or glaucomatous eyes. The proposed method is tested on RIM-ONE r3 database. The experimental results substantially proved that the proposed method achieved 95.29% specificity at 94.59% sensitivity with AUC of 0.869. The proposed method is also compared with existing methods and proved to work better than them.
Key-Words / Index Term
Fundus image, glaucoma, optic disc, optic cup, mask
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