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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE access Ročník 11; s. 70853 - 70864
Hlavní autori:	Kumar, B. Naveen, Mahesh, T. R., Geetha, G., Guluwadi, Suresh
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!