论文标题
通过像素颜色扩增增强视网膜底面图像
Enhancement of Retinal Fundus Images via Pixel Color Amplification
论文作者
论文摘要
我们提出了一种像素颜色扩增理论和增强方法系列，以促进视网膜图像上的分割任务。我们对脱掩基理论基础图像失真模型的新颖重新解释，表明了飞去社区通常使用的三个现有先验和新颖的第四个先验是如何相关的。我们利用该理论来开发一种用于视网膜图像的增强方法家族，包括用于整体图像变亮和变暗的新方法。我们展示了UNSHAP掩盖算法的新型推导。我们将增强方法评估为具有挑战性的多任务分段问题的预处理步骤，并显示出所有任务的性能的大幅度提高，而骰子得分在不重力基准的基线上提高了0.491。我们提供的证据表明，我们的增强预处理可用于不平衡和困难的数据。我们表明，增强功能可以通过将它们组合在一起来执行类平衡。
We propose a pixel color amplification theory and family of enhancement methods to facilitate segmentation tasks on retinal images. Our novel re-interpretation of the image distortion model underlying dehazing theory shows how three existing priors commonly used by the dehazing community and a novel fourth prior are related. We utilize the theory to develop a family of enhancement methods for retinal images, including novel methods for whole image brightening and darkening. We show a novel derivation of the Unsharp Masking algorithm. We evaluate the enhancement methods as a pre-processing step to a challenging multi-task segmentation problem and show large increases in performance on all tasks, with Dice score increases over a no-enhancement baseline by as much as 0.491. We provide evidence that our enhancement preprocessing is useful for unbalanced and difficult data. We show that the enhancements can perform class balancing by composing them together.
