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

点击翻译按钮获取中文摘要

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.