• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Frontiers in Public Health >Computer Vision Malaria Diagnostic Systemsa??Progress and Prospects
【24h】

Computer Vision Malaria Diagnostic Systemsa??Progress and Prospects

机译：计算机视觉疟疾诊断系统的研究进展与展望

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Accurate malaria diagnosis is critical to prevent malaria fatalities, curb overuse of antimalarial drugs, and promote appropriate management of other causes of fever. While several diagnostic tests exist, the need for a rapid and highly accurate malaria assay remains. Microscopy and rapid diagnostic tests are the main diagnostic modalities available, yet they can demonstrate poor performance and accuracy. Automated microscopy platforms have the potential to significantly improve and standardize malaria diagnosis. Based on image recognition and machine learning algorithms, these systems maintain the benefits of light microscopy and provide improvements such as quicker scanning time, greater scanning area, and increased consistency brought by automation. While these applications have been in development for over a decade, recently several commercial platforms have emerged. In this review, we discuss the most advanced computer vision malaria diagnostic technologies and investigate several of their features which are central to field use. Additionally, we discuss the technological and policy barriers to implementing these technologies in low-resource settings world-wide.
机译：准确的疟疾诊断对预防疟疾致死，遏制抗疟药物的过度使用以及促进对其他发烧原因的适当管理至关重要。尽管存在几种诊断测试，但仍然需要快速且高度准确的疟疾分析。显微镜检查和快速诊断测试是可用的主要诊断方式，但它们可能表现出较差的性能和准确性。自动化显微镜平台具有显着改善和标准化疟疾诊断的潜力。这些系统基于图像识别和机器学习算法，保留了光学显微镜的优点，并提供了改进，例如更快的扫描时间，更大的扫描区域以及自动化带来的一致性。虽然这些应用程序已经开发了十多年，但最近出现了一些商业平台。在这篇综述中，我们讨论了最先进的计算机视觉疟疾诊断技术，并研究了对现场使用至关重要的一些功能。此外，我们讨论了在全球资源匮乏的环境中实施这些技术的技术和政策障碍。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号