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We propose a method for improving the accuracy of the optic cup detected from the ARGALI system. This method makes use of key points from the branching points of large vessels, the analysis of intensity variation and kinks from small vessels to obtain an enhanced optic cup. Measures used to assess the detection of the optic cup showed an 11% and 40% improvement in the mean average overlap and relative...
This paper presents a photometric restoration technique that automatically corrects shading within retinal images taken with a fundus camera. The proposed technique is based on the observation that the background of retinal images usually shows flat reflectance variations due to its high similarity in color and texture. It estimates shading through an iterative polynomial interpolation procedure that...
Glaucoma is a leading cause of permanent blindness. ARGALI, an automated system for glaucoma detection, employs several methods for segmenting the optic cup and disc from retinal images, combined using a fusion network, to determine the cup to disc ratio (CDR), an important clinical indicator of glaucoma. This paper discusses the use of SVM as an alternative fusion strategy in ARGALI, and evaluates...
The ratio of the optic cup to disc (CDR) in retinal fundus images is one of the principal physiological characteristics in the diagnosis of glaucoma. Currently the CDR is manually determined which can be subjective and limits its use in mass screening. To automatically extract the disc, a variational level set method is proposed in this paper. For the cup, two methods making use of color intensity...
This paper proposes an algorithm that has been developed for the video-oculograph method. It is used to detect the center of the pupil, extracted from a captured image of an eye acquired by using a CCD camera and a computer with image grabber. The captured eye image is 640 by 480 pixels in size at 8 bits per pixel, in depth. The center of the pupil area could be obtained by applying the proposed algorithms...
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