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Several devices allowing the capture of the retina have recently been proposed. They are composed by optical lenses which can be snapped on Smartphone, providing fundus images with acceptable quality. Thence, the challenge is to perform automatic ocular pathology detection on Smartphone captured fundus images that achieves higher performance detection while respecting timing constraint with respect to the clinical employment. This paper presents a survey of the Smartphone-captured fundus image quality and the existing methods that use them for retinal structures and abnormalities detection. For this purpose, we first summarize the works that evaluate the Smartphone-captures fundus image quality and their FOV (field-of-view). Then, we report the capability to detect abnormalities and ocular pathologies from those fundus images. Thereafter, we propose a flowchart of processing pipeline of detecting methods from Smartphone captured fundus images and we investigate about the implementation environment required to perform the detection of retinal abnormalities. |
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