title: Establishing the macular grading grid by means of fovea centre detection using anatomical-based and visual-based features.
abstract: This paper presents a methodology for establishing the macular grading grid in digital retinal images by means of fovea centre detection. To this effect, visual and anatomical feature-based criteria are combined with the aim of exploiting the benefits of both techniques. First, acceptable fovea centre estimation is obtained by using a priori known anatomical features with respect to the optic disc and the vascular tree. Second, a type of morphological processing is employed in an attempt to improve the obtained fovea centre estimation when the fovea is detectable in the image; otherwise, it is declared indistinguishable and the first result is retained. The methodology was tested on the MESSIDOR and DIARETDB1 databases making use of a distance criterion between the obtained and the real fovea centre. Fovea centres in the brackets between the categories Excellent and Fair (fovea centres primarily accepted as valid in the literature) made up for 98.24% and 94.38% of the cases in the MESSIDOR and DIARETDB1, respectively.
authors.affiliation: Department of Electronic, Computer Science and Automatic Engineering, "La Rábida" High School of Engineering, University of Huelva, 21819 Palos de la Frontera, Spain. Electronic address: arturo.aquino@diesia.uhu.es.
authors.forename: Arturo
authors.initials: A
authors.lastname: Aquino
mesh_terms: D016208:Databases, Factual; D003930:Diabetic Retinopathy / Q000175:diagnosis / Q000473:pathology*; D042241:Early Diagnosis; D005584:Fovea Centralis / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009898:Optic Disk / Q000033:anatomy & histology; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology
keywords: Early diagnosis; Establishing macular grading grid; Fovea segmentation; Retinal diseases; Retinal imaging