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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 6, 2021.
Abstract: Retinal vessel segmentation is an active research area in medical image processing. Several research outcomes on retinal vessel segmentation have emerged in recent years. Each method has its own pros and cons, either in the vessel detection stage or in its extraction. Based on a detailed empirical investigation, a novel retinal vessel extraction architecture is proposed, which makes use of a couple of existing algorithms. In the proposed algorithm, vessel detection is carried out using a cumulative distribution function-based thresholding scheme. The resultant vessel intensities are extracted based on the hysteresis thresholding scheme. Experiments are carried out with retinal images from DRIVE and STARE databases. The results in terms of Sensitivity, Specificity, and Accuracy are compared with five standard methods. The proposed method outperforms all methods in terms of Sensitivity and Accuracy for the DRIVE data set, whereas for STARE, the performance is comparable with the best method.
Farha Fatina Wahid, Sugandhi K, Raju G, Debabrata Swain, Biswaranjan Acharya and Manas Ranjan Pradhan, “A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120663
@article{Fatina Wahid2021,
title = {A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120663},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120663},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {Farha Fatina Wahid and Sugandhi K and Raju G and Debabrata Swain and Biswaranjan Acharya and Manas Ranjan Pradhan}
}
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.