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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Vydáno v:	Microscopy research and technique Ročník 86; číslo 11; s. 1443 - 1460
Hlavní autoři:	Manan, Malik Abdul, Jinchao, Feng, Khan, Tariq M., Yaqub, Muhammad, Ahmed, Shahzad, Chuhan, Imran shabir
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Wiley Subscription Services, Inc 01.11.2023
Témata:	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
On-line přístup:	Získat plný text
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