Computational methods for objective assessment of conjunctival vascularity.
Assessment of vascularity of conjunctiva 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.
Department of Computer Science Electrical Engineering, University of Missouri at Kansas City, Kansas City, MO 64110-2499, USA. reza@umkc.edu
Reza
R
Derakhshani
Sashi K
SK
Saripalle
Plamen
P
Doynov
D003228:Conjunctiva / Q000098:blood supply* / Q000473:pathology; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer; D010781:Photography; D012590:Sclera / Q000473:pathology