• Prof. Prashant Malge
• Miss. Ashwini Kesale

Diabetic retinopathy (DR) is a serious diabetic complication and Microaneurysm (MA) is the earliest lesion in diabetic retinopathy, so early MA detection plays a critical role in diabetic retinopathy diagnosis. In this paper, number of MA has been determined. Initially, pre-processing techniques like green channel extraction, histogram equalization and morphological process have been used. For detection of micro aneurysms, contrast limited adaptive histogram equalization (CLAHE), morphological process, averaging filtering have been used. Classification of DR has been done by linear Support vector machine (SVM). The sensitivity and specificity of DR detection system are observed as 96% and 92% respectively. Finally, we demonstrated extensive experiment results on DiaretDB1 database for the effectiveness of the proposed algorithm.

Microaneurysm detection, diabetic retinopathy, CLAHE, Neural Network

"Detection of Microaneurysm in diabetic retinopathy using fundus image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.a373-a377, November-2023, Available :http://www.jetir.org/papers/JETIR2311055.pdf

"Detection of Microaneurysm in diabetic retinopathy using fundus image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppa373-a377, November-2023, Available at : http://www.jetir.org/papers/JETIR2311055.pdf