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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Veröffentlicht in:	Frontiers in bioengineering and biotechnology Jg. 11; S. 1286966
Hauptverfasser:	Bhansali, Ashok, Patra, Rajkumar, Abouhawwash, Mohamed, Askar, S. S., Awasthy, Mohan, Rao, K. B. V. Brahma
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media SA 19.12.2023 Frontiers Media S.A
Schlagworte:	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
Online-Zugang:	Volltext
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