scholarly journals A Comparative Study of Retinal Image Processing Technique for Blood Vessel Segmentation

2016 ◽  
Vol 5 (4) ◽  
pp. 652-664
Keyword(s):  
Image Processing ◽  
Blood Vessel ◽  
Comparative Study ◽  
Retinal Image ◽  
Processing Technique ◽  
Vessel Segmentation ◽  
Image Processing Technique ◽  
Blood Vessel Segmentation

scholarly journals A Simple Blood Vessel Detection on Retinal Image Using Image Processing Technique

2021 ◽  
Vol 1874 (1) ◽  
pp. 012035
Author(s):  
Siti Nursyafiqah ◽  
Wan Azani Mustafa ◽  
Syed Zulkarnain Syed Idrus ◽  
Mohd Aminudin Jamlos
Keyword(s):  
Image Processing ◽  
Blood Vessel ◽  
Retinal Image ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Blood Vessel Detection ◽  
Vessel Detection

scholarly journals DETECTION AND SEGMENTATION OF OPTIC DISC IN FUNDUS IMAGES

2018 ◽  
Vol 10 (5) ◽  
pp. 20
Author(s):  
Ramesh C. ◽  
Udayakumar E. ◽  
Yogeshwaran K.
Keyword(s):  
Image Processing ◽  
Optic Disc ◽  
Retinal Image ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Optic Disk ◽  
Curve Evolution ◽  
Fundus Images ◽  
Medical Field ◽  
Shape And Size

Objective: Image processing technique is utilized in the medical field widely nowadays. Hence, therefore, this technique is used to extract the different features like blood vessels, optic disk, macula, fovea etc. automatically of the retinal image of eye.Methods: This paper presents a simple and fast algorithm using Mathematical Morphology to find the fovea of fundus retinal image. The image for analysis is obtained from the DRIVE database. Also, this paper is enhanced to detect the Diabetic Retinopathy disease occurring in the eye.Results: Detection of optic disc boundary becomes important for the diagnosis of glaucoma. The iterative curve evolution was stopped at the image boundaries where the energy was minimum.Conclusion: The changes in the shape and size of the optic disc can be used to detect glaucoma and also cup ratio can be used as a measure of glaucoma.

Blood vessel segmentation of retinal image using Clifford matched filter and Clifford convolution

2019 ◽  
Vol 78 (24) ◽  
pp. 34839-34865 ◽  
Author(s):  
Somasis Roy ◽  
Anirban Mitra ◽  
Sudipta Roy ◽  
Sanjit Kumar Setua
Keyword(s):  
Blood Vessel ◽  
Retinal Image ◽  
Matched Filter ◽  
Vessel Segmentation ◽  
Blood Vessel Segmentation
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