Title :
Computational methods for objective assessment of conjunctival vascularity
Author :
Derakhshani, R. ; Saripalle, S.K. ; Doynov, P.
Author_Institution :
Dept. of Comput. Sci. Electr. Eng., Univ. of Missouri at Kansas City, Kansas City, MO, USA
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
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.
Keywords :
biomedical optical imaging; blood vessels; cancer; eye; image colour analysis; medical image processing; neural nets; artificial neural networks; color digital imaging; computational methods; conjunctival vascularity; correlation coefficient; diagnostic applications; objective assessment; prognostic applications; Arteries; Artificial neural networks; Cities and towns; Humans; Lenses; Training; Conjunctiva; Databases, Factual; Humans; Image Processing, Computer-Assisted; Neural Networks (Computer); Photography; Sclera;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346223
