Retinal Image Enhancement based on the Human Visual System

描述（由申请人提供）：本项目的目的是证明一种方法，用于提高标准眼底照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。标准的视网膜图像通常遭受照明伪影、反射率中的大动态范围和模糊。在这个项目中，Kestrel将在各种眼底相机系统上展示其图像质量增强算法，包括数字非散瞳设备，散瞳胶片相机和散瞳百万像素仪器。我们的目标是通过眼科医生和训练有素的眼科技术人员进行的受控评估表明，我们处理的图像可显著改善图像质量，从而提高对糖尿病视网膜病变和年龄相关性黄斑变性等疾病的视网膜图像进行分级或筛查的灵敏度和特异性。这个软件的商业潜力是巨大的。一种低成本的提高图像质量的方法将是所有视网膜相机制造商感兴趣的。该项目将表明，任何现有眼底相机都可以实现改进，从而为所有未来和现有仪器打开市场。

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.