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In clinical diagnosis, a grade indicating the severity of nuclear cataract is often manually assigned by a trained ophthalmologist to a patient after comparing the lens' opacity severity in his/her slit-lamp images with a set of standard photos. This grading scheme is often subjective and time-consuming. In this paper, a novel computer-aided diagnosis method via ranking is proposed to facilitate nuclear...
Glaucoma is the second leading cause of blindness worldwide. The risk of glaucoma can be determined by calculating the cup to disc ratio in retinal fundus images. To accurately detect the optic cup, kinks or bends in small and medium vessels are important indicators of the cup boundary. In this paper, we present a method of detecting such vessels, through the extraction of patches and generation of...
The genome-wide association (GWA) study is the latest approach in the development of genetic studies and is renowned for its widespread success in identifying disease variants within the genome for various common diseases. It is a highly popular study amongst geneticists worldwide, evident from the numerous GWA studies conducted in laboratories all over the world. This paper introduces various GWA...
Cataract is the leading cause of blindness worldwide. Two automatic grading systems are presented in this paper for nuclear cataract and cortical cataract diagnosis respectively. Model-based approach was applied to detect anatomical structure in slit-lamp images. Features were extracted based on the lens structure and severity of nuclear cataract was predicted using support vector machines (SVM) regression...
Glaucoma is the one of the two major causes of blindness, which can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A multimodality fusion approach for neuroretinal cup detection improves the accuracy of the boundary estimation...
With the advances of computer technology, more and more computer-aided diagnosis (CAD) systems have been developed to provide the ldquosecond opinionrdquo. This paper reports an automatic fundus image classification technique that is designed to screen out the severely degraded fundus images that cannot be processed by traditional CAD systems. The proposed technique classifies fundus images based...
Glaucoma is the second leading cause of blindness. Glaucoma can be diagnosed through measurement of neuro-retinal optic cup-to-disc ratio (CDR). Automatic calculation of optic cup boundary is challenging due to the interweavement of blood vessels with the surrounding tissues around the cup. A Convex Hull based Neuro-Retinal Optic Cup Ellipse Optimization algorithm improves the accuracy of the boundary...
An automatic diagnosis system of nuclear cataract is presented in this paper. Nuclear cataract is graded according to the severity of opacity using slit-lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model (ASM). Based on the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine (SVM) regression...
An approach to automatically diagnose nuclear cataract based on the slit-lamp image is proposed in this paper. Model-based approach is investigated to detect robust lens structure. Based on the detected lens structure, the mean intensity, the color information on the posterior subcapsular reflex and visual axis profile are extracted as the grading features. Support vector machine (SVM) regression...
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