论文标题
使用图像处理的三重量方法用于视网膜血管分割
A Trio-Method for Retinal Vessel Segmentation using Image Processing
论文作者
论文摘要
内部视网膜神经元是视网膜中最重要的部分，它们通过视网膜血管提供血液。本文主要着重于使用三重预处理方法分割视网膜血管。考虑了驱动器数据库，并通过Sobel和Pruning通过Gabor过滤，高斯模糊和边缘检测进行了预处理。分割由2个提议的U-NET架构驱动。根据所有标准性能指标，比较了这两种体系结构。预处理产生的各种有趣的结果影响了UNET体系结构进行分割的结果。这种实时部署可以帮助通过更好的细分和检测进行有效的图像预处理。
Inner Retinal neurons are a most essential part of the retina and they are supplied with blood via retinal vessels. This paper primarily focuses on the segmentation of retinal vessels using a triple preprocessing approach. DRIVE database was taken into consideration and preprocessed by Gabor Filtering, Gaussian Blur, and Edge Detection by Sobel and Pruning. Segmentation was driven out by 2 proposed U-Net architectures. Both the architectures were compared in terms of all the standard performance metrics. Preprocessing generated varied interesting results which impacted the results shown by the UNet architectures for segmentation. This real-time deployment can help in the efficient pre-processing of images with better segmentation and detection.
