Contributor(s)Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà
Age-related Macular Degeneration
Diagnosis Aid System
Local Binary Patterns
TEORIA DE LA SEÑAL Y COMUNICACIONES
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This work investigates discrimination capabilities in the texture of fundus images to differentiate between pathological and healthy images. For this purpose, the performance of Local Binary Patterns (LBP) as a texture descriptor for retinal images has been explored and compared with other descriptors such as LBP filtering (LBPF) and local phase quantization (LPQ). The goal is to distinguish between diabetic retinopathy (DR), agerelated macular degeneration (AMD) and normal fundus images analysing the texture of the retina background and avoiding a previous lesion segmentation stage. Five experiments (separating DR from normal, AMD from normal, pathological from normal, DR from AMD and the three different classes) were designed and validated with the proposed procedure obtaining promising results. For each experiment, several classifiers were tested. An average sensitivity and specificity higher than 0.86 in all the cases and almost of 1 and 0.99, respectively, for AMD detection were achieved. These results suggest that the method presented in this paper is a robust algorithm for describing retina texture and can be useful in a diagnosis aid system for retinal disease screening.
NILS Science and Sustainability Programme (010-ABEL-IM-2013)
Ministerio de Economía y Competitividad of Spain, Project ACRIMA (TIN2013-46751-R)
Morales, S.; Engan, K.; Naranjo Ornedo, V.; Colomer, A. (2015). Retinal Disease Screening through Local Binary Patterns. IEEE Journal of Biomedical and Health Informatics. (99):1-8. doi:10.1109/JBHI.2015.2490798.