Deep learning-based analysis of macaque corneal sub-basal nerve fibers in confocal microscopy images
Deep learning-based analysis of macaque corneal sub-basal nerve fibers in confocal microscopy images
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DOI：
10.1186/s40662-020-00192-5
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发表时间：
2020-05-08
期刊：
影响因子：
4.2
通讯作者：
Mankowski, Joseph L.
中科院分区：
文献类型：
--
作者：
Oakley, Jonathan D.;Russakoff, Daniel B.;Mankowski, Joseph L.
开发并验证一种基于深度学习的方法，利用体内共聚焦显微镜（IVCM）全自动分析猕猴角膜基底下神经。方法采用IVCM采集35只猕猴108张图像。利用22只猕猴的58张图像，对不同的深度卷积神经网络（CNN）结构进行了相对于人工追踪的基底下神经自动分析。剩下的图像被用来独立评估相关性和观察者之间相对于三个读者的表现。结果读者与最佳CNN的决定系数相关评分平均为0.80。在观察者间比较中，三种专家阅读者与自动方法的相互相关系数（ICCs）分别为0.75、0.85和0.92。4名观察者之间的ICC值为0.84，与CNN和个人读者之间的平均值相同。结论IVCM图像中基于深度学习的基底下神经分割与猕猴数据中的人工分割具有高度到非常高的相关性，且在不同的读卡者之间难以区分。由于角膜基底下神经的定量测量是疾病筛查和管理的重要生物标志物，因此报告的工作为使用IVCM的各种研究和临床研究提供了实用价值。
Background To develop and validate a deep learning-based approach to the fully-automated analysis of macaque corneal sub-basal nerves using in vivo confocal microscopy (IVCM). Methods IVCM was used to collect 108 images from 35 macaques. 58 of the images from 22 macaques were used to evaluate different deep convolutional neural network (CNN) architectures for the automatic analysis of sub-basal nerves relative to manual tracings. The remaining images were used to independently assess correlations and inter-observer performance relative to three readers. Results Correlation scores using the coefficient of determination between readers and the best CNN averaged 0.80. For inter-observer comparison, inter-correlation coefficients (ICCs) between the three expert readers and the automated approach were 0.75, 0.85 and 0.92. The ICC between all four observers was 0.84, the same as the average between the CNN and individual readers. Conclusions Deep learning-based segmentation of sub-basal nerves in IVCM images shows high to very high correlation to manual segmentations in macaque data and is indistinguishable across readers. As quantitative measurements of corneal sub-basal nerves are important biomarkers for disease screening and management, the reported work offers utility to a variety of research and clinical studies using IVCM.