论文标题
角膜显微镜的深度学习
Deep Learning for Cornea Microscopy Blind Deblurring
论文作者
论文摘要
该项目的目的是建立一种深入学习解决方案，该解决方案用于医学检查，该解决方案是deblurs角膜扫描。眼睛的球形形状可防止奥科植物学家的图像完全清晰。我们的方法配备了一堆来自共焦图像的角膜，我们的方法是构建一个模型，该模型使用SR（超级分辨率）网络对图像进行升级。
The goal of this project is to build a deep-learning solution that deblurs cornea scans, used for medical examination. The spherical shape of the eye prevents ophtamologist from having completely sharp image. Provided with a stack of corneas from confocal images, our approach is to build a model that performs an upscaling of the images using an SR (Super Resolution) Network.
