title: Closed angle glaucoma detection in RetCam images.
abstract: Closed/Open angle glaucoma classification is important for glaucoma diagnosis. RetCam is a new imaging modality that captures the image of iridocorneal angle for the classification. However, manual grading and analysis of the RetCam image is subjective and time consuming. In this paper, we propose a system for intelligent analysis of iridocorneal angle images, which can differentiate closed angle glaucoma from open angle glaucoma automatically. Two approaches are proposed for the classification and their performances are compared. The experimental results show promising results.
authors.affiliation: Institute for Infocomm Research, A*STAR, 1 Fusionopolis Way, #21-01 Connexis, Singapore 138632. jcheng@i2r.a-star.edu.sg
authors.forename: Jun
authors.initials: J
authors.lastname: Cheng
authors.forename: Jiang
authors.initials: J
authors.lastname: Liu
authors.forename: Beng Hai
authors.initials: BH
authors.lastname: Lee
authors.forename: Damon Wing Kee
authors.initials: DW
authors.lastname: Wong
authors.forename: Fengshou
authors.initials: F
authors.lastname: Yin
authors.forename: Tin
authors.initials: T
authors.lastname: Aung
authors.forename: Mani
authors.initials: M
authors.lastname: Baskaran
authors.forename: Perera
authors.initials: P
authors.lastname: Shamira
authors.forename: Tien Yin
authors.initials: TY
authors.lastname: Wong
mesh_terms: D015812:Glaucoma, Angle-Closure / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D010781:Photography