Semantic segmentation of retinal exudates using a residual encoder–decoder architecture in diabetic retinopathy

Exudates are a common sign of diabetic retinopathy, which is a disease that affects the blood vessels in the retina. Early detection of exudates is critical to avoiding vision problems through continuous screening and treatment. In traditional clinical practice, the involved lesions are manually det...

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Bibliographic Details
Published in:	Microscopy research and technique Vol. 86; no. 11; pp. 1443 - 1460
Main Authors:	Manan, Malik Abdul, Jinchao, Feng, Khan, Tariq M., Yaqub, Muhammad, Ahmed, Shahzad, Chuhan, Imran shabir
Format:	Journal Article
Language:	English
Published:	United States Wiley Subscription Services, Inc 01.11.2023
Subjects:	Accuracy Artificial neural networks Benchmarks Blood vessels Coders Computer architecture Deep learning Diabetes Diabetes mellitus Diabetic retinopathy Diagnosis Edema Exudates Exudation Health services Image contrast Image processing Image segmentation Lesions Machine learning Medical imaging Neural networks Ophthalmology Parameters Performance enhancement Retina Retinal images Retinopathy Screening Semantic segmentation Semantics Vision retinal image data augmentation exudates residual network semantic segmentation diabetic retinopathy convolution neural network
ISSN:	1059-910X, 1097-0029, 1097-0029
Online Access:	Get full text
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