Low-cost, portable, computer assisted imaging for diabe*

描述（由申请人提供）：我们开发了一种便携式，低成本，患者友好的视网膜成像设备，Delft Retinascan，基于双波长扫描激光技术。它不需要药物瞳孔扩张或闪光照明，并且该设备的原型成本低于1100美元。我们利用它获得了正常受试者的高空间分辨率视网膜图像，典型的获取时间为0.1s。我们和其他人已经证明，使用数码相机和互联网连接进行大规模早期诊断是安全有效的。我们还表明，计算机辅助诊断算法可以通过用标准的市售眼底相机拍摄的双视野非立体彩色眼底照片来评估糖尿病视网膜病变，这与视网膜专家的结论高度一致。潜在地，这些技术可以结合起来为糖尿病视网膜病变提供低成本、高质量、对患者友好的早期诊断系统。然而，在临床上应用这种低成本的相机和数字诊断系统之前，需要进行临床验证。

DESCRIPTION (provided by applicant): We have developed a portable, low-cost, patient-friendly, retinal imaging device, the Delft Retinascan, based on dual wavelength scanning laser technology. It does not require pharmacologic pupil dilation or flash illumination, and the prototype costs of the device were less than $1100. We have utilized it to acquire retinal images in normal subjects at high spatial resolution with a typical acquisition time of 0.1s. We and others have shown that large scale early diagnosis using digital cameras and internet connectivity is safe and effective. We have also shown that computer assisted diagnostic algorithms can assess diabetic retinopathy from two-field non-stereo color fundus photographs made with standard commercially available fundus cameras, with a high degree of agreement with retinal specialists. Potentially, these techniques can be combined for a low-cost, high quality, patient friendly, early diagnosis system for diabetic retinopathy. However, clinical validation is required before this low-cost camera and digital diagnostic system can be implemented clinically. Our specific aims are: 1. to technically validate the low-cost Delft Retinascan camera system for non-invasive imaging of diabetic retinopathy; 2. to assess and validate the clinical utility of the Delft Retinascan by collaborating with the Wisconsin Reading Center (WRC). The WRC will be responsible for reading and assessing images acquired with the Retinascan and compare them with ETDRS standard 7-field stereo fundus photographs; 3. and to evaluate the improvement in performance of the addition of computer assisted diagnostic algorithms on the images acquired with the Delft Retinascan. We have assembled a team representing expertise in diabetic retinopathy screening over the internet, optical engineering, retinal imaging, secure online medical image servers, image analysis, and epidemiology, consisting of research oriented ophthalmologists, physicists, computer engineers, and biostatisticians, and who are poised to translate the above techniques into a clinically practical system. Our overall aim is to validate and optimize a low-cost, high quality, patient friendly imaging system for the early diagnosis of diabetic retinopathy.