Retinal Image Enhancement based on the Human Visual System

描述(申请人提供)：这个项目的目标是演示一种方法，以提高用标准眼底相机拍摄的视网膜图像的质量。Kestrel开发了一系列算法，通过实施一种受人类视觉系统机制启发的方法来执行图像视网膜增强。标准的视网膜图像经常会出现光照伪影、反射率动态范围大、模糊等问题。在这个项目中，Kestrel将在各种眼底相机系统上演示其图像质量增强算法，包括数字非散光设备、散光胶片相机和散光百万像素仪器。我们的目标是通过眼科医生和训练有素的眼科技术人员的受控评估，表明我们处理的图像显著改善了图像质量，进而提高了对糖尿病视网膜病变和老年性黄斑变性等疾病的视网膜图像进行分级或筛选的敏感性和特异性。这个软件的商业潜力是巨大的。一种低成本的改善图像质量的方法将引起所有视网膜相机制造商的兴趣。该项目将表明，任何现有的眼底相机都可以实现改进，从而为所有未来和现有的仪器打开市场。

DESCRIPTION (provided by applicant): The objective of this project is to demonstrate a methodology for improving the quality of retinal images taken with standard fundus camera. Kestrel has developed a family of algorithms that perform image retinal enhancement through the implementation of a method that is inspired from human visual system mechanisms. Standard retinal images often suffer from illumination artifacts, large dynamic range in the reflectance, and blurring. In this project, Kestrel will demonstrate its image quality enhancement algorithms on a wide variety of fundus camera systems, including a digital non-mydriatic device, a mydriatic film camera, and a mydriatic mega-pixel instrument. Our objective is to show, through controlled evaluations by ophthalmologists and highly trained ophthalmic technicians, that our processed images result in significant improvements in image quality and which in turn would result in improved sensitivity and specificity for grading or screening retinal images for diseases such as diabetic retinopathy and age-related macular degeneration. The commercial potential of this software is immense. A low-cost means for improving image quality will be of interest to all retinal camera manufactures. The project will show that improvement can be realized for any existing fundus camera, thereby opening up the market to all future and existing instruments.