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Multi-Layer Preprocessing and U-Net with Residual Attention Block for Retinal Blood Vessel Segmentation.

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第一作者： Ahmed,Alsayat

第一单位： Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72341, Saudi Arabia.

作者： Ahmed,Alsayat ^[1] ; Mahmoud,Elmezain ^[2] ; Saad,Alanazi ^[1] ; Meshrif,Alruily ^[1] ; Ayman Mohamed,Mostafa ^[3] ; Wael,Said ^[4]

作者单位： Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72341, Saudi Arabia. ^[1] Computer Science Division, Faculty of Science, Tanta University, Tanta 31527, Egypt.;Computer Science Department, College of Computer Science and Engineering, Taibah University, Yanbu 966144, Saudi Arabia. ^[2] Information Systems Department, College of Computer and Information Sciences, Jouf University, Sakaka 72341, Saudi Arabia. ^[3] Computer Science Department, Faculty of Computers and Informatics, Zagazig University, Zagazig 44511, Egypt.;Computer Science Department, College of Computer Science and Engineering, Taibah University, Medina 42353, Saudi Arabia. ^[4]

关键词 GAN data augmentation data imputation noise removal retinal image segmentation

DOI 10.3390/diagnostics13213364

PMID 37958260

发布时间 2023-11-22

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Diagnostics (Basel, Switzerland)

2023年13卷21期

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Multi-Layer Preprocessing and U-Net with Residual Attention Block for Retinal Blood Vessel Segmentation.

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Multi-Layer Preprocessing and U-Net with Residual Attention Block for Retinal Blood Vessel Segmentation.

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