Retinal based Automated Healthcare Framework via Deep Learning

Pritom Das R, Rakshitha G, I. Juvanna, D. Venkat Subramanian
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引用次数: 1

Abstract

Developing countries have limited access to low cost retinal images which hinders the progress in preventing needless blindness. Portable advancements are opening new doors to human services. Handheld ophthalmoscopes and smartphone fundus photography solutions are already providing promising solutions to low cost and portability. In this paper, we have discussed a new way to retinal fundus photography based on a Head Mounted Device(HMD) concept. HMDs will allow to obtain automated retinal images from patients. These images acts as biomarkers and helps in detection of chronic and long term diseases. Deep learning techniques are utilised to automate disease detection and patients are given corrective suggestions through their smartphones. We are translating technology into clinical care in the dawn of smart healthcare.
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基于视网膜的深度学习自动化医疗框架
发展中国家获得低成本视网膜图像的机会有限,这阻碍了在预防不必要失明方面取得进展。便携技术的进步为人类服务打开了新的大门。手持式检眼镜和智能手机眼底摄影解决方案已经为低成本和便携性提供了有前途的解决方案。本文讨论了一种基于头戴式设备(HMD)概念的视网膜眼底摄影新方法。头戴式显示器可以自动获取患者的视网膜图像。这些图像作为生物标志物,有助于检测慢性和长期疾病。深度学习技术被用于自动化疾病检测,并通过智能手机向患者提供纠正建议。在智能医疗的曙光中,我们正在将技术转化为临床护理。
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