Abstract
In this research work, an exhaustive review has been done in the context of understanding the algorithms involved in building diabetic retinopathy systems. The study is important because with time India has become “Diabetic Capital” of the world. Due to diabetics, eyes of the people at large are getting impacted, and it plays a major role in blinding people and accelerating comorbidities. This study found that experts take into account specific features such as blood vessel area to detect abnormalities in eyes, and for this, they are primarily using fundus image processing algorithm in combination with statistical/machine/deep learning models. In this paper, we have conducted a review of the methods for automatically detecting and classifying diabetic retinopathy. This review points out that there are primarily three approaches that authors are applying for detecting diabetic retinopathy, and a meticulous view of algorithms is given for detecting diabetic retinopathy.
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Datta, P., Das, P., Kumar, A. (2022). Techniques in Detecting Diabetic Retinopathy: A Review. In: Sarma, H.K.D., Balas, V.E., Bhuyan, B., Dutta, N. (eds) Contemporary Issues in Communication, Cloud and Big Data Analytics. Lecture Notes in Networks and Systems, vol 281. Springer, Singapore. https://doi.org/10.1007/978-981-16-4244-9_34
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DOI: https://doi.org/10.1007/978-981-16-4244-9_34
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