DocumentCode
2941559
Title
Closed angle glaucoma detection in RetCam images
Author
Jun Cheng ; Jiang Liu ; Beng Hai Lee ; Wong, Damon Wing Kee ; Fengshou Yin ; Tin Aung ; Baskaran, Mani ; Shamira, P. ; Tien Yin Wong
Author_Institution
Inst. for Infocomm Res., A*STAR, Singapore, Singapore
fYear
2010
fDate
Aug. 31 2010-Sept. 4 2010
Firstpage
4096
Lastpage
4099
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.
Keywords
artificial intelligence; biomedical optical imaging; diseases; eye; image classification; medical image processing; RetCam images; closed angle glaucoma detection; closed/open angle glaucoma classification; glaucoma diagnosis; intelligent analysis; iridocorneal angle; Cornea; Image edge detection; Imaging; Iris; Lenses; Sensitivity; Transforms; Glaucoma, Angle-Closure; Humans; Photography;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location
Buenos Aires
ISSN
1557-170X
Print_ISBN
978-1-4244-4123-5
Type
conf
DOI
10.1109/IEMBS.2010.5627290
Filename
5627290
Link To Document