Abnormality detection in retinal image by individualized background learning

摘要

Computer-aided lesion detection (CAD) techniques, which provide potential for automatic early screening of retinal pathologies, are widely studied in retinal image analysis. While many CAD approaches based on lesion samples or lesion features can well detect pre-defined lesion types, it remains challenging to detect various abnormal regions (namely abnormalities) from retinal images. In this paper, we try to identify diverse abnormalities from a retinal test image by finely learning its individualized retinal background (IRB) on which retinal lesions superimpose.