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以人工智能为基础的决策支持系统,用于使用in vivo对焦显微镜图像诊断阿坎萨摩巴角膜炎

Alisa Lincke¹, Jenny Roth², António Filipe Macedo^2,3

¹Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden.

Translational vision science & technology

|November 27, 2023

概括

一个人工智能系统有助于通过使用体内共聚焦显微镜 (IVCM) 图像来诊断Acanthamoeba角膜炎 (AK). 这个人工智能决策支持系统预处理图像,减少了专家的选时间.

科学领域:

眼科医生眼科眼科
医疗成像医学成像
人工智能的人工智能

背景情况:

在生物共聚焦显微镜 (IVCM) 对于角膜评估至关重要,但缺乏独立的诊断能力.
需要自动诊断支持,以提高IVCM在角膜疾病的临床效用.
阿坎萨摩巴角膜炎 (AK) 是一种严重的感染,需要及时准确的诊断.

研究的目的:

开发和评估基于人工智能 (AI) 的决策支持系统 (DSS),用于自动诊断阿坎萨摩巴角膜炎 (AK).
利用体内共聚焦显微镜 (IVCM) 图像作为AI驱动诊断系统的输入.

主要方法:

实现了基于AI的DSS的深度学习和图像处理工作流.
使用85名患者数据集 (47,734张IVCM图像) 训练和验证模型,并对26名额外的患者进行测试 (21,236张图像).
在整个开发过程中纳入基于规则的决策和专家意见.

主要成果:

人工智能-DSS在将艺术品与真实图像分开时获得了93%的准确性,在分类角膜层时获得了90%的准确性.
该系统以95%的准确度预测健康与患病的角膜.
AK检测准确率为84%,在定位诊断区域的准确率为76.5%.

结论:

基于人工智能的DSS有效预处理IVCM图像,分离文物和分类角膜层,从而缩短查时间.
需要进一步的研究,以提高直接从原始IVCM图像中检测AK的准确性.
自动化DSS为使用IVCM成像诊断AK的专家提供了宝贵的帮助.

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