Teng T, Lefley M, Claremont D
Academic Biomedical Engineering Research Group, School of Design, Engineering & Computing, Bournemouth University, Dorset, UK.
Med Biol Eng Comput. 2002 Jan;40(1):2-13. doi: 10.1007/BF02347689.
Patients with diabetes require annual screening for effective timing of sight-saving treatment. However, the lack of screening and the shortage of ophthalmologists limit the ocular health care available. This is stimulating research into automated analysis of the reflectance images of the ocular fundus. Publications applicable to the automated screening of diabetic retinopathy are summarised. The review has been structured to mimic some of the processes that an ophthalmologist performs when examining the retina. Thus image processing tasks, such as vessel and lesion location, are reviewed before any intelligent or automated systems. Most research has been undertaken in identification of the retinal vasculature and analysis of early pathological changes. Progress has been made in the identification of the retinal vasculature and the more common pathological features, such as small aneurysms and exudates. Ancillary research into image preprocessing has also been identified. In summary, the advent of digital data sets has made image analysis more accessible, although questions regarding the assessment of individual algorithms and whole systems are only just being addressed.
糖尿病患者需要每年进行筛查，以便及时进行挽救视力的治疗。然而，筛查的缺乏以及眼科医生的短缺限制了可获得的眼部保健服务。这促使人们对眼底反射图像的自动分析展开研究。本文总结了适用于糖尿病视网膜病变自动筛查的相关出版物。该综述的结构模仿了眼科医生检查视网膜时所执行的一些流程。因此，在介绍任何智能或自动化系统之前，先对诸如血管和病变定位等图像处理任务进行综述。大多数研究都集中在视网膜血管系统的识别以及早期病理变化的分析上。在视网膜血管系统的识别以及更常见的病理特征（如小动脉瘤和渗出物）的分析方面已经取得了进展。还确定了图像预处理的辅助研究。总之，数字数据集的出现使图像分析变得更加容易，尽管有关单个算法和整个系统评估的问题才刚刚开始得到解决。
