Automatic classification of the interferential tear film lipid layer using colour texture analysis

被引:20
作者
Remeseiro, B. [1 ]
Penas, M. [1 ]
Barreira, N. [1 ]
Mosquera, A. [2 ]
Novo, J. [1 ]
Garcia-Resua, C. [3 ]
机构
[1] Univ A Coruna, Dept Comp, La Coruna 15071, Spain
[2] Univ Santiago de Compostela, Dept Elect & Comp, Santiago De Compostela 15782, Spain
[3] Univ Santiago de Compostela, Escuela Opt & Optometria, Santiago De Compostela 15782, Spain
关键词
Tear film lipid layer; Guillon categories; Texture analysis; Machine learning; Principal component analysis; SPACE;
D O I
10.1016/j.cmpb.2013.04.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The tear film lipid layer is heterogeneous among the population. Its classification depends on its thickness and can be done using the interference pattern categories proposed by Guillon. This papers presents an exhaustive study about the characterisation of the interference phenomena as a texture pattern, using different feature extraction methods in different colour spaces. These methods are first analysed individually and then combined to achieve the best results possible. The principal component analysis (PCA) technique has also been tested to reduce the dimensionality of the feature vectors. The proposed methodologies have been tested on a dataset composed of 105 images from healthy subjects, with a classification rate of over 95% in some cases. (C) 2013 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:93 / 103
页数:11
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