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• W4285138312 abstract "This work aims to develop a hybrid image examination system to extract and evaluate the Optic Disc (OD) from the Age-related Macular Degeneration (AMD) and Non-AMD class Digital Fundus Retinal Image (DFRI). This work implements an image pre-processing through Shannon’s Entropy and Social Group Optimization (SE+SGO) based thresholding and image post-processing with Level Set Segmentation (LSS). A relative study among the extracted OD and the ground-truth is then executed to compute the vital Picture Similarity Parameters (PSP). This study also presents a detailed pixel level data analysis practice on the extracted OD. Finally, the performance of the LSS is then validated against the existing segmentation techniques, such as Chan-Vese, Active-Contour and k-means clustering. The proposed work is executed on the iChallenge-AMD-2018 DFRI (400 images) and the results confirm that, proposed hybrid tool helps to achieve better values of Jaccard (86.82%), Dice (91.78%), Accuracy (98.94%), Precision (92.86%), Sensitivity (94.06%), and Specificity (99.46%)." @default.
• W4285138312 created "2022-07-14" @default.
• W4285138312 creator A5053663161 @default.
• W4285138312 creator A5058475882 @default.
• W4285138312 date "2022-05-20" @default.
• W4285138312 modified "2023-10-14" @default.
• W4285138312 title "An Image Examination System for Retinal Optic Disc Mining and Analysis With Social Group Optimization Algorithm" @default.
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• W4285138312 doi "https://doi.org/10.4018/ijsir.300370" @default.
• W4285138312 hasPublicationYear "2022" @default.
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