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Enhanced glaucoma detection using U-Net and U-Net+ architectures using deep learning techniques
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DOI：10.1016/j.pdpdt.2025.104621.png)
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摘要
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• 高级深度学习技术：利用U-Net和U-Net+进行有效的青光眼检测。
• 高精度：通过鲁棒深度学习架构实现可靠诊断。
• 增强的检测能力：集成前馈层以提高性能。
• 临床影响：提供早期检测的可靠工具，改善患者预后。
Keyword:
Glaucoma
Retinal intra-ocular region
Frame networks
U-NET layers
DRISHTI-GS
DRIONS-DB
HRF
期刊
IF:
2.6
论文数:
4.8K
被引数:
9.8K
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