Redefining Retinal Lesion Segmentation: A Quantum Leap With DL-UNet Enhanced Auto Encoder-Decoder for Fundus Image Analysis

The first diagnosis of diabetic retinopathy (DR) must include lesion segmentation. As it takes a lot of time and effort to label lesions, automatic segmentation methods have to be created manually. The degree of the retina's degenerative lesions determines how severe diabetic retinopathy is. A...

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Veröffentlicht in:	IEEE access Jg. 11; S. 70853 - 70864
Hauptverfasser:	Kumar, B. Naveen, Mahesh, T. R., Geetha, G., Guluwadi, Suresh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Abnormalities Algorithms Artificial neural networks Coders convolutional neural network Convolutional neural networks Decoding Deep learning Diabetes Diabetic retinopathy Diseases encoder-decoder network Encoders-Decoders Encoding Exudation fundus images Image analysis Image enhancement Image segmentation lesion segmentation Lesions Machine learning Network analysis Neural networks patch generation Retina spatial attention mechanism
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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