Optimization Techniques Are Best Choice to Segment Blood Vessels from Retinal Fundus Images
N.C. Santosh Kumar1, Y.Radhika2
1SN.C.Santosh Kumar, Department of CSE, GIT, Gitam University, Vizag, Andhra Pradesh, India
2Dr.Y.Radhika, Department of CSE,GIT, Gitam University, Vizag, Andhra Pradesh, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 4799-4812 | Volume-9 Issue-1, October 2019 | Retrieval Number: F92341088619/2019©BEIESP | DOI: 10.35940/ijeat.F9234.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The mostly affected disease which has been a curse to human kind is diabetes. This disease, irrespective of the age, causes extreme impact upon the eyes of the patients indicating abnormalities which manifests in tree-like structured blood vessels of the retina. It is so important to diagnose such patients with diabetes at the initial stage so as to save them from reaching blindness. Blood vessel segmentation in retinal fundus images is an adequate way and takes a critical role in medication and diagnosis of distinct retinal-related diseases and disorders. In this paper, a comprehensive review of various categories of segmentation techniques is presented with main focus on proving the magnificence of optimization techniques as the right choice in the process segmentation. The effectiveness of this work is straightened in relative study of discrete methods.
Keywords: Retinal fundus images, blood vessels segmentation, ant colony optimization, particle swarm optimization, bee colony optimization, genetic algorithm.