title: Defining the Optimal Region of Interest for Hyperemia Grading in the Bulbar Conjunctiva.
abstract: Conjunctival hyperemia or conjunctival redness is a symptom that can be associated with a broad group of ocular diseases. Its levels of severity are represented by standard photographic charts that are visually compared with the patient's eye. This way, the hyperemia diagnosis becomes a nonrepeatable task that depends on the experience of the grader. To solve this problem, we have proposed a computer-aided methodology that comprises three main stages: the segmentation of the conjunctiva, the extraction of features in this region based on colour and the presence of blood vessels, and, finally, the transformation of these features into grading scale values by means of regression techniques. However, the conjunctival segmentation can be slightly inaccurate mainly due to illumination issues. In this work, we analyse the relevance of different features with respect to their location within the conjunctiva in order to delimit a reliable region of interest for the grading. The results show that the automatic procedure behaves like an expert using only a limited region of interest within the conjunctiva.
authors.affiliation: VARPA Group, Department of Computer Science, University of A Coruna, A Coruna, Spain.
authors.forename: María Luisa
authors.initials: ML
authors.lastname: Sánchez Brea
authors.affiliation: VARPA Group, Department of Computer Science, University of A Coruna, A Coruna, Spain.
authors.forename: Noelia
authors.identifier: 0000-0003-0961-2057
authors.initials: N
authors.lastname: Barreira Rodríguez
authors.affiliation: Artificial Vision Group, Department of Electronics and Computer Science, University of Santiago de Compostela, Santiago de Compostela, Spain.
authors.forename: Antonio
authors.initials: A
authors.lastname: Mosquera González
authors.affiliation: School of Optometry and Vision Sciences, Cardiff University, Wales, UK.
authors.forename: Katharine
authors.initials: K
authors.lastname: Evans
authors.affiliation: Optometry Group, Department of Applied Physics, University of Santiago de Compostela, Santiago de Compostela, Spain.
authors.forename: Hugo
authors.initials: H
authors.lastname: Pena-Verdeal
mesh_terms: D000465:Algorithms; D001808:Blood Vessels / Q000473:pathology; D003228:Conjunctiva / Q000000981:diagnostic imaging / Q000503:physiopathology*; D016208:Databases, Factual; D005123:Eye / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D006940:Hyperemia / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D000069550:Machine Learning; D015588:Observer Variation; D009907:Optometry / Q000379:methods; D010363:Pattern Recognition, Automated; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index