An Integrated XI-UNet for Accurate Retinal Vessel Segmentation

被引:0
作者
Aruna Vinodhini, C. [1 ]
Sabena, S. [2 ]
机构
[1] Anna Univ, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India
[2] Anna Univ, Reg Ctr, Dept Comp Sci & Engn, Tirunelveli, Tamil Nadu, India
关键词
Blood vessel segmentation; XI-UNet; patch extraction; de-hazing; combined pooling; IMAGES;
D O I
10.1142/S0218126623501827
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Segmentation of blood vessels captured using a fundus camera is the cornerstone for the medical examination of several retinal vascular disorders. In recent research studies, vessel segmentation models focus on deep neural learning. To overlook the segmentation of the toughest retinal vessels like thin vessels, a new neural network architecture is developed based on U-Net integrated with the idea of depth-wise separable convolution and the Inception network incorporated with the sparsity of information. The developed XI-UNet network is trained and tested on DRIVE, STARE and CHASE_DB1 public datasets. The performance and the achievements of the XI-UNet network are greater compared to the prevalent methods.
引用
收藏
页数:13
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