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视网膜血管自动动动脉/静脉分类方法:一篇综述
Qihan Chen1, Jianqing Peng2, Shen Zhao1
1School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
概括
本综述涵盖了自动视网膜动脉静脉分类方法从2003-2022. 未来的研究应该将深度学习与拓信息相结合,以改善早期疾病诊断.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 计算机科学 计算机科学
背景情况:
- 自动视网膜动脉静脉分类有助于眼科医生在早期诊断疾病.
- 深度学习和基于拓图的方法是主要的方法.
- 提出了从2003年到2022年的方法的全面审查.
研究的目的:
- 审查和比较自动视网膜动脉静脉分类方法.
- 分析公共数据集和注释开发.
- 建立一个全面的分类挑战评估系统.
主要方法:
- 对各种分类技术进行比较分析.
- 公共数据集的分类与注释开发表.
- 开发一个全面的分类挑战评估系统.
主要成果:
- 比较表总结了不同方法的性能.
- 公共数据集的注释开发表.
- 识别研究趋势和随着时间推移的演变.
结论:
- 深度学习与拓信息的整合是未来重要的研究方向.
- 本综述为理解视网膜动脉静脉分类的演变提供了基础.
- 拟议的评估系统解决了该领域当前的挑战.
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