Glaucoma ocular disease is the second topmost reason for irreversible visual impairment around the world. This malady can be cured and permanent blindness can be prevented by timely diagnosis and treatment. This study is an attempt to analyse the current status of automated glaucoma diagnosis systems. Existing systems have been analysed on the base of ophthalmic imaging technology, capability to detect glaucoma at initial or latter stages, detection strategy and performance. Analysis revealed several research gaps mainly in automated glaucoma detection based on Fundus and Optical Coherence Tomography (OCT) ophthalmic imaging technologies. More accurate diagnosis of glaucoma at early and curable stages is possible by bridging the identified gaps.

中文翻译：

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一项确定现有自动化系统在初始和可治愈阶段检测青光眼的局限性的研究

青光眼眼病是全球不可逆视力损害的第二大原因。这种疾病可以通过及时诊断和治疗来治愈并防止永久性失明。本研究试图分析自动青光眼诊断系统的现状。已经根据眼科成像技术、在初始或后期阶段检测青光眼的能力、检测策略和性能对现有系统进行了分析。分析揭示了几个主要在基于眼底和光学相干断层扫描 (OCT) 眼科成像技术的自动青光眼检测方面的研究空白。通过弥合已识别的差距，可以在早期和可治愈的阶段更准确地诊断青光眼。