ABSTRACT.Purpose: To develop and evaluate a simple and rapid algorithm for optic disc measurements on digital fundus photographs, relying on the macula-disc centre distance as a reference when converting length expressed in pixels to metric distance. Methods: Measurements were performed on fundus photographs from 68 normal subjects, acquired using five different cameras. The magnification factor and actual size in lm of 1 pixel was known for only one camera. The measurements from this camera were compared to corresponding measurements from a confocal scanning laser ophthalmoscope. Results: Using the described algorithm, no significant differences in mean disc or cup size were observed between the tested cameras, despite differences in magnification factor (range 0.5-2.5). There were no significant differences between disc and cup measurements obtained with the confocal scanning laser ophthalmoscope and those obtained with the described algorithm in the 20 subjects examined. Conclusion: The algorithm described in the current study provided clinically relevant measurements of optic disc parameters. The final program can be used directly on the acquired images, with the examined subject still available for re-examination.

. Purpose:  Retinal images acquired by means of digital photography are often used for evaluation and documentation of the ocular fundus, especially in patients with diabetes, glaucoma or age‐related macular degeneration. The clinical usefulness of an image is highly dependent on its quality. We set out to develop and evaluate an automatic method of evaluating the quality of digital fundus photographs. Methods:  A method for making a numerical quantification of image sharpness and illumination was developed using Matlab™ image analysis functions. Based on their sharpness and illumination measures, 1000 fundus photographs, randomly selected from a clinical database, were assigned to four predefined quality groups (not acceptable, acceptable, good, very good). Six independent observers, comprising three experienced ophthalmologists and three ophthalmic nurses with extensive experience in fundus image acquisition, classified a selection of 100 of these images into the corresponding quality groups. Results:  Automatic quality evaluation was more sensitive than evaluation by human observers in terms of ability to discriminate between good and very good images. The median concordance between the six human observers and the automatic evaluation was substantial (kappa = 0.64). Conclusions:  The proposed method provides an objective quality assessment of digital fundus photographs which agrees well with evaluations made by qualified human observers and which may be useful in clinical practice.