Level-set based adaptive-active contour segmentation technique with long short-term memory for diabetic retinopathy classification

Diabetic Retinopathy (DR) is a major type of eye defect that is caused by abnormalities in the blood vessels within the retinal tissue. Early detection by automatic approach using modern methodologies helps prevent consequences like vision loss. So, this research has developed an effective segmentat...

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Vydané v:	Frontiers in bioengineering and biotechnology Ročník 11; s. 1286966
Hlavní autori:	Bhansali, Ashok, Patra, Rajkumar, Abouhawwash, Mohamed, Askar, S. S., Awasthy, Mohan, Rao, K. B. V. Brahma
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media SA 19.12.2023 Frontiers Media S.A
Predmet:	Accuracy adaptive-active counter model Algorithms Bioengineering and Biotechnology Blood vessels Boundary conditions Classification Deep learning Diabetes Diabetes mellitus Diabetic retinopathy gray level co-occurrence matrix Image processing level set method with improved boundary indicator function Long short-term memory Neural networks Optimization Retinopathy Segmentation Visual impairment Wavelet transforms adaptive-active counter model level set method with improved boundary indicator function gray level co-occurrence matrix diabetic retinopathy long short term memory
ISSN:	2296-4185, 2296-4185
On-line prístup:	Získať plný text
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