Matches in SemOpenAlex for { <https://semopenalex.org/work/W3213072252> ?p ?o ?g. }
Showing items 1 to 83 of
83
with 100 items per page.
- W3213072252 abstract "Diabetes is exploding and pandemic all over the world. High glucose peaks cause vessel wall damage, especially in the microvasculature. The retina is particularly susceptible since it is the most oxygen-consuming tissue in the body. Retinal deterioration leads to blindness, and it is estimated that 4% of diabetics will go blind at some point. Microaneurysms, haemorrhages, hard and soft exudates are few biomarkers on retinal vasculature, to identify Diabetic retinopathy. The diameter or width of retinal vessels is also a key indicator of blood flow and metabolism in the retina. The goal of this research is to employ deep learning algorithms to efficiently segment, classify and assess the retinal vascular diameters of a healthy and diabetic individual and to look at how these methodologies contribute to the identification of diabetic retinopathy and may be used as a predictor of disease diagnosis. U-Net architecture for segmentation of vessels, SVM for classification of vessels as arteries and veins and VAMPIRE for the assessment of vascular diameters are proposed in this research work." @default.
- W3213072252 created "2021-11-22" @default.
- W3213072252 creator A5003994707 @default.
- W3213072252 creator A5009323532 @default.
- W3213072252 creator A5034350851 @default.
- W3213072252 creator A5061011679 @default.
- W3213072252 creator A5085395081 @default.
- W3213072252 creator A5090190003 @default.
- W3213072252 date "2021-10-01" @default.
- W3213072252 modified "2023-09-25" @default.
- W3213072252 title "Deep Learning Methods for the Assessment of Vascular Diameters for Diabetic Retinopathy Screening" @default.
- W3213072252 cites W1841361427 @default.
- W3213072252 cites W2051834526 @default.
- W3213072252 cites W2052710217 @default.
- W3213072252 cites W2112637299 @default.
- W3213072252 cites W2117953248 @default.
- W3213072252 cites W2119107710 @default.
- W3213072252 cites W2125014106 @default.
- W3213072252 cites W2130266732 @default.
- W3213072252 cites W2142707127 @default.
- W3213072252 cites W2168261002 @default.
- W3213072252 cites W2895202718 @default.
- W3213072252 cites W3102146568 @default.
- W3213072252 cites W3155045972 @default.
- W3213072252 doi "https://doi.org/10.1109/gcat52182.2021.9587870" @default.
- W3213072252 hasPublicationYear "2021" @default.
- W3213072252 type Work @default.
- W3213072252 sameAs 3213072252 @default.
- W3213072252 citedByCount "0" @default.
- W3213072252 crossrefType "proceedings-article" @default.
- W3213072252 hasAuthorship W3213072252A5003994707 @default.
- W3213072252 hasAuthorship W3213072252A5009323532 @default.
- W3213072252 hasAuthorship W3213072252A5034350851 @default.
- W3213072252 hasAuthorship W3213072252A5061011679 @default.
- W3213072252 hasAuthorship W3213072252A5085395081 @default.
- W3213072252 hasAuthorship W3213072252A5090190003 @default.
- W3213072252 hasConcept C118487528 @default.
- W3213072252 hasConcept C119767625 @default.
- W3213072252 hasConcept C134018914 @default.
- W3213072252 hasConcept C154945302 @default.
- W3213072252 hasConcept C169760540 @default.
- W3213072252 hasConcept C2776689232 @default.
- W3213072252 hasConcept C2777093970 @default.
- W3213072252 hasConcept C2778313320 @default.
- W3213072252 hasConcept C2779829184 @default.
- W3213072252 hasConcept C2780827179 @default.
- W3213072252 hasConcept C2780929884 @default.
- W3213072252 hasConcept C41008148 @default.
- W3213072252 hasConcept C555293320 @default.
- W3213072252 hasConcept C71924100 @default.
- W3213072252 hasConcept C86803240 @default.
- W3213072252 hasConceptScore W3213072252C118487528 @default.
- W3213072252 hasConceptScore W3213072252C119767625 @default.
- W3213072252 hasConceptScore W3213072252C134018914 @default.
- W3213072252 hasConceptScore W3213072252C154945302 @default.
- W3213072252 hasConceptScore W3213072252C169760540 @default.
- W3213072252 hasConceptScore W3213072252C2776689232 @default.
- W3213072252 hasConceptScore W3213072252C2777093970 @default.
- W3213072252 hasConceptScore W3213072252C2778313320 @default.
- W3213072252 hasConceptScore W3213072252C2779829184 @default.
- W3213072252 hasConceptScore W3213072252C2780827179 @default.
- W3213072252 hasConceptScore W3213072252C2780929884 @default.
- W3213072252 hasConceptScore W3213072252C41008148 @default.
- W3213072252 hasConceptScore W3213072252C555293320 @default.
- W3213072252 hasConceptScore W3213072252C71924100 @default.
- W3213072252 hasConceptScore W3213072252C86803240 @default.
- W3213072252 hasLocation W32130722521 @default.
- W3213072252 hasOpenAccess W3213072252 @default.
- W3213072252 hasPrimaryLocation W32130722521 @default.
- W3213072252 hasRelatedWork W110576239 @default.
- W3213072252 hasRelatedWork W1809594647 @default.
- W3213072252 hasRelatedWork W2103072249 @default.
- W3213072252 hasRelatedWork W2114709213 @default.
- W3213072252 hasRelatedWork W2579905261 @default.
- W3213072252 hasRelatedWork W3029563123 @default.
- W3213072252 hasRelatedWork W3043102626 @default.
- W3213072252 hasRelatedWork W761131545 @default.
- W3213072252 hasRelatedWork W2562755469 @default.
- W3213072252 hasRelatedWork W2593962225 @default.
- W3213072252 isParatext "false" @default.
- W3213072252 isRetracted "false" @default.
- W3213072252 magId "3213072252" @default.
- W3213072252 workType "article" @default.