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 :
بازگشت