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Glaucoma is currently diagnosed by glaucoma specialists using specialized imaging devices like HRT and OCT. Fundus imaging is a modality widely used in primary healthcare. An automatic glaucoma diagnosis system based on fundus image can be deployed to primary healthcare clinics and has potential for early disease diagnosis. A mass glaucoma screening program can also be facilitated using such a system...
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...
Accurate diagnosis and treatment of various pathologic conditions can be achieved by integrating multimodal imaging systems that furnish complementary information to improve patient management. The availability of high-resolution tomography systems, fast computers, and image reconstruction algorithms has improved disease diagnosis and treatment management. As medical practice moves into the molecular...
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