Diabetic Retinopathy is damage to the retina caused by complications of diabetes mellitus. Exudates are the primary sign of Diabetic Retinopathy identified on the opthalmoscope as white or yellowish areas with varying sizes, shapes and locations in the retina. Early detection can potentially reduce the risk of blindness. Diabetic retinopathy diagnosis for early-stage detection used a manual or semi-automated system that only an ophthalmologist can do it. This project proposed an automatic analysis of diabetic retinopathy and lesion of the eye in the retinal region using image processing techniques. The proposed technique is using thresholding technique. The data is taken from the DIRECTDB1 database. Pre-processing is applied first and then the image is segmented into 8 x 8 regions. An image histogram is then been calculated at each region to look for the maximum number of pixels for each intensity level. By comparing normal and exudate regions, the best threshold is found. The proposed technique is validated based on the accuracy, specificity, and sensitivity of exudate detection from the ground truth image reference. The mean from the range of the abnormal region of interest (ROI) is also calculated whether it is within range of the optimal value. In conclusion, adaptive thresholding is the method of choice to develop an automated detection of diabetic retinopathy. The result shows an accuracy of 65.79%, sensitivity is 31.58%, and specificity is 100%. The best segmentation and classification performance is achieved in the range of abnormal region ROI which is 0.35 to 0.55.
Segmentation of Diabetic Retinopathy Based on Retinal Fundus Images Using Thresholding Technique
Advances in Engineering res
Proceedings of the Multimedia University Engineering ; 2022 ; Cyberjaya and Melaka, Malaysia July 25, 2022 - July 27, 2022
Proceedings of the Multimedia University Engineering Conference (MECON 2022) ; Kapitel : 17 ; 164-173
23.12.2022
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
New automatic multi-level thresholding technique for segmentation of thermal images
British Library Online Contents | 1997
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