Retinal Image Registration and Comparison for Clinical Decision Support

Di Xiao, Janardhan Vignarajan, Jane Lock, Shaun Frost, Mei-Ling Tay-Kearney, Yogesan Kanagasingam



For eye diseases, such as glaucoma and age-related macular degeneration (ARMD), involved in long-term degeneration procedure, longitudinal comparison of retinal images is a common step for reliable diagnosis of these kinds of diseases.


To provide a retinal image registration approach for longitudinal retinal image alignment and comparison.


Two image registration solutions were proposed for facing different image qualities of retinal images to make the registration methods more robust and feasible in a clinical application system.


Thirty pairs of longitudinal retinal images were used for the registration test. The experiments showed both solutions provided good performance for the accurate image registrations with efficiency.


We proposed a set of retinal image registration solutions for longitudinal retinal image observation and comparison targeting a clinical application environment.

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