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How to cite (IEEE):
D. Toresa, M. Shahril, N. Harun, J. Bakar, & H. Amnur
"Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm," JOIV : International Journal on Informatics Visualization, vol. 5, no. 3, , pp. 242-247, Sep. 2021.
https://doi.org/10.30630/joiv.5.3.664
How to cite (APA):
Toresa, D., Shahril, M., Harun, N., Bakar, J., & Amnur, H.
(2021).
Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm.
JOIV : International Journal on Informatics Visualization, 5(3), 242-247.
https://doi.org/10.30630/joiv.5.3.664
How to cite (Chicago):
Toresa, Dafwen, Shahril, Mohamad, Harun, Nor, Bakar, Juhaida, AND Amnur, Hidra.
"Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm" JOIV : International Journal on Informatics Visualization [Online], Volume 5 Number 3 (19 September 2021)
https://doi.org/10.30630/joiv.5.3.664
How to cite (Vancouver):
Toresa D, Shahril M, Harun N, Bakar J, & Amnur H .
Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm.
JOIV : International Journal on Informatics Visualization [Online]. 2021 Sep;
5(3):242-247.
https://doi.org/10.30630/joiv.5.3.664
How to cite (Harvard):
Toresa, D., Shahril, M., Harun, N., Bakar, J., & Amnur, H.
,2021.
Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm.
JOIV : International Journal on Informatics Visualization, [Online] 5(3), pp. 242-247.
https://doi.org/10.30630/joiv.5.3.664
How to cite (MLA8):
Toresa, Dafwen, Mohamad Azrul Edzwan Shahril, Nor Hazlyna Harun, Juhaida Abu Bakar, & Hidra Amnur.
"Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm." JOIV : International Journal on Informatics Visualization [Online], 5.3 (2021): 242-247. Web. 29 Nov. 2023
, https://doi.org/10.30630/joiv.5.3.664
BibTex Citation Data :
@article{JOIV664,
author = {Dafwen Toresa and Mohamad Shahril and Nor Harun and Juhaida Bakar and Hidra Amnur},
title = {Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm},
journal = {JOIV : International Journal on Informatics Visualization},
volume = {5},
number = {3},
year = {2021},
keywords = {Diabetes; diabetic retinopathy; image segmentation; hard exudates; fundus images.},
abstract = {Diabetic Retinopathy (DR) is one of diabetes complications that affects our eyes. Hard Exudate (HE) are known to be the early signs of DR that potentially lead to blindness. Detection of DR automatically is a complicated job since the size of HE is very small. Besides, our community nowadays lack awareness on diabetic where they do not know that diabetes can affect eyes and lead to blindness if regular check-up is not performed. Hence, automated detection of HE known as Eye Retinal Imaging System (EyRis) was created to focus on detecting the HE based on fundus image. The purpose of this system development is for early detection of the symptoms based on retina images captured using fundus camera. Through the captured retina image, we can clearly detect the symptoms that lead to DR. In this study, proposed Watershed segmentation method for detecting HE in fundus images. Top-Hat and Bottom-Hat were use as enhancement technique to improve the quality of the image. This method was tested on 15 retinal images from the Universiti Sains Malaysia Hospital (HUSM) at three different stages: Normal, NPDR, and PDR. Ten of these images have abnormalities, while the rest are normal retinal images. The evaluation of the segmentation images would be compared by Sensitivity, F-score and accuracy based on medical expert's hand drawn ground truth. The results achieve accuracy 0.96 percent with 0.99 percent sensitivity for retinal images.},
issn = {2549-9904}, pages = {242--247}, doi = {10.30630/joiv.5.3.664},
url = {https://joiv.org/index.php/joiv/article/view/664}
}
Refworks Citation Data :
@article{{JOIV}{664}, author = {Toresa, D., Shahril, M., Harun, N., Bakar, J., Amnur, H.}, title = {Automated Detection and Counting of Hard Exudates for Diabetic Retinopathy by using Watershed and Double Top-Bottom Hat Filtering Algorithm}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {5}, number = {3}, year = {2021}, doi = {10.30630/joiv.5.3.664}, 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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is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.