Abstract
Diabetic Retinopathy (DR) is one of the emerging diseases among the adults all over the world. DR is an eye complication occurs due to the prolonged high glucose level in the blood and it affects the retinal blood vessels present at the back of the eye. DR results in vision loss which cannot be reversed. Earlier detection of DR is necessary to maintain good vision among the DR patients throughout their lives. The number of persons with poor vision due to DR increases rapidly. Computerized automatic diagnosis of DR helps the ophthalmologists to reduce manual errors and tedious work. This paper provides the brief survey about the existing methods of segmentation techniques which is the one of the most important stages in the automatic computerized diagnosis of DR. This review article will help the researchers to work on the disadvantages of the existing methods to enhance overall performance in terms of accuracy and AUC.
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Monisha Birlin, T., Divya, C. (2022). Comparison of Various Segmentation Techniques in Diabetic Retinopathy-A Review. In: Gunjan, V.K., Zurada, J.M. (eds) Modern Approaches in Machine Learning & Cognitive Science: A Walkthrough. Studies in Computational Intelligence, vol 1027. Springer, Cham. https://doi.org/10.1007/978-3-030-96634-8_7
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DOI: https://doi.org/10.1007/978-3-030-96634-8_7
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