A review on automatic analysis techniques for color fundus photographs

Abstract

In this paper, we give a review on automatic image processing tools to recognize diseases causing specific distortions in the human retina. After a brief summary of the biology of the retina, we give an overview of the types of lesions that may appear as biomarkers of both eye and non-eye diseases. We present several state-of-the-art procedures to extract the anatomic components and lesions in color fundus photographs and decision support methods to help clinical diagnosis. We list publicly available databases and appropriate measurement techniques to compare quantitatively the performance of these approaches. Furthermore, we discuss on how the performance of image processing-based systems can be improved by fusing the output of individual detector algorithms. Retinal image analysis using mobile phones is also addressed as an expected future trend in this field.

Recent Development on Detection Methods for the Diagnosis of Diabetic Retinopathy

“…The F1-score can be calculated as an equal weight of both SE and precision: 2TP/(2TP + FP + FN). In addition, an AUC of 1 indicates a good performance of the method while an AUC of 0.5 shows a moderate performance [21,22].…”

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