María S. Millán

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This paper presents a comparative study on the use of no-reference quality metrics for eye fundus imaging. We center on auto-focusing and quality assessment as key applications for the correct operation of a fundus imaging system. Four state-of-the-art no-reference metrics were selected for the study. From these, a metric based of Rényi anisotropy yielded(More)
Retinal images are essential clinical resources for the diagnosis of retinopathy and many other ocular diseases. Because of improper acquisition conditions or inherent optical aberrations in the eye, the images are often degraded with blur. In many common cases, the blur varies across the field of view. Most image deblurring algorithms assume a(More)
Retinal images are widely used for diagnostic purposes by ophthalmolo-gists. Therefore, these images are suitable for digital image analysis for their visual enhancement and pathological risk or damage detection. Here, we implement a lu-minosity and contrast enhancement technique based on domain knowledge. We also review and analyze a previous approach in(More)
The ISNT rule and differentiation of normal from glaucomatous eyes " , Arch. A contribution of image processing to the diagnosis of diabetic retinopathy – detection of exudates in color fundus images of the human retina " , IEEE T. Med. Cup-to-disc ratio of the optic disc by image analysis to assist diagnosis of glaucoma risk and evolution, " in ABSTRACT:(More)
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