基于改进U-Net的视盘杯分割研究

Mao Qian, Jiang Minshan, Wei-ge Jing
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引用次数: 0

摘要

在青光眼的诊断中,基于数字眼底图像分割视杯和视盘是一种常用的诊断方法。为了准确分割杯盘,我们提出了一种基于改进U-Net的杯盘分割方法。与传统的U-Net相比,利用残差块改进下采样部分,利用卷积部分改进跳跃连接,使网络能够获得更充分的特征信息。在DRISHTI-GS数据集上,视盘分割模型和光杯分割模型的Dice和IOU分别达到98.3%和97.2%、93.2%和88.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the segmentation of optic disc and cup based on modified U-Net
: In the diagnosis of glaucoma, segmentation of optic cup and optic disc based on digital fundus image is a common diagnostic method. In order to segment the cup and disc accurately, we proposed a segmentation method based on the improved U-Net. Compared with the traditional U-Net, a residual block was used to improve the down sampling part, and convolution part was used to improve the skip connection, so that the network could obtain more sufficient feature information. The Dice and IOU of the optic disc segmentation model and the optic cup segmentation model on DRISHTI-GS data set reached 98.3% and 97.2%, 93.2% and 88.5%.
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