Paper Info
Title
On the analysis of local and global features for hyperemia grading.
Abstract
In optometry, hyperemia is the accumulation of blood flow in the conjunctival tissue. Dry eye syndrome or allergic conjunctivitis are two of its main causes. Its main symptom is the presence of a red hue in the eye that optometrists evaluate according to a scale in a subjective manner. In this paper, we propose an automatic approach to the problem of hyperemia grading in the bulbar conjunctiva. We compute several image features on images of the patients' eyes, analyse the relations among them by using feature selection techniques and transform the feature vector of each image to the value in the adequate range by means of machine learning techniques. We analyse different areas of the conjunctiva to evaluate their importance for the diagnosis. Our results show that it is possible to mimic the experts' behaviour through the proposed approach.
Year
DOI
Venue
2016
10.1117/12.2268804
Proceedings of SPIE
Keywords
Field
DocType
Hyperemia grading,Optometry,Feature selection,Regression,Medical imaging
Allergic conjunctivitis,Computer vision,Feature vector,Grading (education),Feature selection,Pattern recognition,Medical imaging,Feature (computer vision),Computer science,Hue,Artificial intelligence,Bulbar conjunctiva
Conference
Volume
ISSN
Citations 
10341
0277-786X
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
L Sánchez101.35
Noelia Barreira218217.47
N. Sánchez300.34
Antonio Mosquera González411516.72
Hugo Pena-Verdeal532.52
E. Yebra-Pimentel6234.64