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Abstract #46238 Published in IGR 13-2

ORIGA(-light): an online retinal fundus image database for glaucoma analysis and research

Zhang Z; Yin FS; Liu J; Wong WK; Tan NM; Lee BH; Cheng J; Wong TY
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2010; 2010: 3065-3068


Retinal fundus image is an important modality to document the health of the retina and is widely used to diagnose ocular diseases such as glaucoma, diabetic retinopathy and age-related macular degeneration. However, the enormous amount of retinal data obtained nowadays mostly stored locally; and the valuable embedded clinical knowledge is not efficiently exploited. In this paper we present an online depository, ORIGA(-light), which aims to share clinical groundtruth retinal images with the public; provide open access for researchers to benchmark their computer-aided segmentation algorithms. An in-house image segmentation and grading tool is developed to facilitate the construction of ORIGA(-light). A quantified objective benchmarking method is proposed, focusing on optic disc and cup segmentation and Cup-to-Disc Ratio (CDR). Currently, ORIGA(-light) contains 650 retinal images annotated by trained professionals from Singapore Eye Research Institute. A wide collection of image signs, critical for glaucoma diagnosis, are annotated. We will update the system continuously with more clinical ground-truth images. ORIGA(-light) is available for online access upon request.

Z. Zhang. Institute for Infocomm Research, A*STAR, Singapore. Email: zzhang@i2r.a-star.edu.sg


Classification:

15 Miscellaneous
6.8.2 Posterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)



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