A review of retinal blood vessels extraction techniques: challenges, taxonomy, and future trends

The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular ailment, high blood pressure, arteriosclerosis, and age-related macular degeneration. The manual inspection of retin...

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Bibliographic Details
Published in:Pattern analysis and applications : PAA 2019-08, Vol.22 (3), p.767-802
Main Authors: Khan, Khan Bahadar, Khaliq, Amir A., Jalil, Abdul, Iftikhar, Muhammad Aksam, Ullah, Najeeb, Aziz, Muhammad Waqar, Ullah, Kifayat, Shahid, Muhammad
Format: Article
Language:English
Subjects:
Abnormalities
Algorithms
Arteriosclerosis
Blood vessels
Computer Science
Diabetic retinopathy
Eye (anatomy)
Glaucoma
Hypertension
Inspection
Macular degeneration
Medical personnel
Pattern Recognition
Retina
Survey
Taxonomy
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Summary:The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular ailment, high blood pressure, arteriosclerosis, and age-related macular degeneration. The manual inspection of retinal vasculature is an extremely challenging and tedious task for medical experts due to the complex structure of an eye, tiny blood vessels, and variation in vessels width. Several automatic retinal vessels extraction techniques have been proposed in contemporary literature, which assist ophthalmologists in the timely identification of an eye disorders. However, due to the fast evolution of such techniques, a comprehensive survey is needed. This survey presents a comprehensive review of such techniques, strategies, and algorithms presented to date. The techniques are classified into logical groups based on the underlying methodology employed for retinal vessel extraction. The performance of existing techniques is reported on the publicly accessible datasets in term of various performance measures, providing a valuable comparison among the techniques. Thus, this survey presents a valuable resource for researchers working toward automatic extraction of retinal vessels.
ISSN:1433-7541
1433-755X
DOI:10.1007/s10044-018-0754-8