Supporting data for "Harnessing the Power of Retinal Nerve Fiber Layer Optical Texture Analysis and Deep Learning in Glaucoma"
Version 1This dataset supports the thesis "Harnessing the Power of Retinal Nerve Fiber Layer Optical Texture Analysis and Deep Learning in Glaucoma." The research aims to leverage RNFL Optical Texture Analysis (ROTA) and deep learning techniques for glaucoma detection, classification, and progression tracking. The thesis comprises three main components: pattern analysis of ROTA in early glaucoma subjects, analysis of fundus images for glaucomatous disease diagnosis, and analysis of sequential ROTA maps f
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This dataset supports the thesis "Harnessing the Power of Retinal Nerve Fiber Layer Optical Texture Analysis and Deep Learning in Glaucoma." The research aims to leverage RNFL Optical Texture Analysis (ROTA) and deep learning techniques for glaucoma detection, classification, and progression tracking. The thesis comprises three main components: pattern analysis of ROTA in early glaucoma subjects, analysis of fundus images for glaucomatous disease diagnosis, and analysis of sequential ROTA maps f