Computational methods for objective assessment of conjunctival vascularity

Computational methods for objective assessment of conjunctival vascularity

Assessment of vascularity of conjunctival has many diagnostic and prognostic applications, thus creation of computational methods for its fast and objective assessment is of importance. Here we provide two different methods for estimation of conjunctiva's vascularity from color digital images,...

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Bibliographische Detailangaben
Hauptverfasser: Derakhshani, R., Saripalle, S. K., Doynov, P.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Arteries
Artificial neural networks
Cities and towns
Conjunctiva - blood supply
Conjunctiva - pathology
Databases, Factual
Humans
Image Processing, Computer-Assisted - methods
Lenses
Neural Networks (Computer)
Photography
Sclera - pathology
Training
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Beschreibung
Zusammenfassung:Assessment of vascularity of conjunctival has many diagnostic and prognostic applications, thus creation of computational methods for its fast and objective assessment is of importance. Here we provide two different methods for estimation of conjunctiva's vascularity from color digital images, with our best results showing a correlation coefficient of 0.89 between the predicted and ground truth values using a committee of artificial neural networks.
ISSN:1094-687X
1557-170X
1558-4615
DOI:10.1109/EMBC.2012.6346223