Name
Abstract | ||
|---|---|---|
Dry eye is a symptomatic disease which affects a wide range of population and has a negative impact on their daily activities. Its diagnosis can be achieved by analyzing the interference patterns of the tear film lipid layer and by classifying them into one of the Guillon categories. The manual process done by experts is not only affected by subjective factors but is also very time consuming. In this paper we propose a general methodology to the automatic classification of tear film lipid layer, using color and texture information to characterize the image and feature selection methods to reduce the processing time. The adequacy of the proposed methodology was demonstrated since it achieves classification rates over 97% while maintaining robustness and provides unbiased results. Also, it can be applied in real time, and so allows important time savings for the experts. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/JBHI.2013.2294732 | Biomedical and Health Informatics, IEEE Journal of |
Keywords | Field | DocType |
biomedical optical imaging,diseases,eye,feature selection,image classification,image texture,medical image processing,Guillon categories,automatic classification,classification rates,color information,daily activities,diagnosis,dry eye,feature selection methods,general methodology,image characterization,interference patterns,manual process,processing time reduction,subjective factors,symptomatic disease,tear film lipid layer classification,texture information,Feature selection,Guillon categories,machine learning,tear film lipid layer,textural features | Computer vision,Population,Feature selection,Pattern recognition,Computer science,Robustness (computer science),Artificial intelligence,Interference (wave propagation) | Journal |
Volume | Issue | ISSN |
18 | 4 | 2168-2194 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
11 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Beatriz Remeseiro | 1 | 50 | 11.87 |
| Verónica Bolón-Canedo | 2 | 476 | 33.04 |
| Diego Peteiro-Barral | 3 | 70 | 9.07 |
| Amparo Alonso-Betanzos | 4 | 885 | 76.98 |
| Bertha Guijarro-Berdiñas | 5 | 296 | 34.36 |
| Antonio Mosquera González | 6 | 115 | 16.72 |
| Manuel G. Penedo | 7 | 185 | 35.91 |
| Noelia Sánchez-Maroño | 8 | 406 | 25.39 |
| Bolon-Canedo, V. | 9 | 1 | 0.35 |
| Peteiro-Barral, D. | 10 | 2 | 0.75 |
| Alonso-Betanzos, A. | 11 | 8 | 0.94 |