论文标题
在眼底图像上学习了自动糖尿病性视网膜病变检测的预处理
Learned Pre-Processing for Automatic Diabetic Retinopathy Detection on Eye Fundus Images
论文作者
论文摘要
糖尿病性视网膜病是世界上工作年龄人群失明的主要原因。本文的主要目的是通过实现眼睛眼底图像的预处理阶段来提高糖尿病性视网膜病检测的准确性。为此，我们依靠最近的发现表明，在倒强度域上使用图像的应用等于照明补偿。受这项工作的启发，我们提出了一个阴影去除层，该层使我们能够学习特定任务的预处理功能。我们表明，学习预处理功能可以改善网络在糖尿病性视网膜病变检测任务上的性能。
Diabetic Retinopathy is the leading cause of blindness in the working-age population of the world. The main aim of this paper is to improve the accuracy of Diabetic Retinopathy detection by implementing a shadow removal and color correction step as a preprocessing stage from eye fundus images. For this, we rely on recent findings indicating that application of image dehazing on the inverted intensity domain amounts to illumination compensation. Inspired by this work, we propose a Shadow Removal Layer that allows us to learn the pre-processing function for a particular task. We show that learning the pre-processing function improves the performance of the network on the Diabetic Retinopathy detection task.
