RT journal article
T1 Automatic CDR Estimation for Early Glaucoma Diagnosis
A1 Fernández Granero, Miguel Ángel
A1 Sarmiento Vega, Auxiliadora
A1 Sánchez Morillo, Daniel
A1 Jiménez Carmona, Soledad
A1 Alemany Márquez, Pedro María
A1 Fondón García, Irene
A2 Ingeniería en AutomáticaElectrónica, Arquitectura y Redes de Computadores
AB Glaucoma is a degenerative disease that constitutes the second cause of blindness in developed countries. Although it cannot be cured, its progression can be prevented through early diagnosis. In this paper, we propose a new algorithm for automatic glaucoma diagnosis based on retinal colour images. We focus on capturing the inherent colour changes of optic disc (OD) and cup borders by computing several colour derivatives in CIE L∗a∗b∗ colour space with CIE94 colour distance. In addition, we consider spatial information retaining these colour derivatives and the original CIE L∗a∗b∗ values of the pixel and adding other characteristics such as its distance to the OD centre. The proposed strategy is robust due to a simple structure that does not need neither initial segmentation nor removal of the vascular tree or detection of vessel bends. The method has been extensively validated with two datasets (one public and one private), each one comprising 60 images of high variability of appearances. Achieved class-wise-averaged accuracy of 95.02% and 81.19% demonstrates that this automated approach could support physicians in the diagnosis of glaucoma in its early stage, and therefore, it could be seen as an opportunity for developing low-cost solutions for mass screening programs.
PB Wiley
SN 2040-2309
YR 2017
FD 2017
LK http://hdl.handle.net/10498/35239
UL http://hdl.handle.net/10498/35239
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 22-sep-2026