title: Robust multi-scale superpixel classification for optic cup localization.
abstract: This paper presents an optimal model integration framework to robustly localize the optic cup in fundus images for glaucoma detection. This work is based on the existing superpixel classification approach and makes two major contributions. First, it addresses the issues of classification performance variations due to repeated random selection of training samples, and offers a better localization solution. Second, multiple superpixel resolutions are integrated and unified for better cup boundary adherence. Compared to the state-of-the-art intra-image learning approach, we demonstrate improvements in optic cup localization accuracy with full cup-to-disc ratio range, while incurring only minor increase in computing cost.
authors.affiliation: iMED Ocular Programme, Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632, Singapore; School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore. Electronic address: nmtan@i2r.a-star.edu.sg.
authors.forename: Ngan-Meng
authors.initials: NM
authors.lastname: Tan
authors.affiliation: iMED Ocular Programme, Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632, Singapore.
authors.forename: Yanwu
authors.initials: Y
authors.lastname: Xu
authors.affiliation: School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
authors.forename: Wooi Boon
authors.initials: WB
authors.lastname: Goh
authors.affiliation: iMED Ocular Programme, Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632, Singapore.
authors.forename: Jiang
authors.initials: J
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D005901:Glaucoma / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009898:Optic Disk / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity
keywords: Glaucoma; Model selection; Optic cup localization; Sparse learning; Superpixel classification