Two-Dimensional Plane for Multi-Scale Quantification of Corneal Subbasal Nerve Tortuosity.
Two-Dimensional Plane for Multi-Scale Quantification of Corneal Subbasal Nerve Tortuosity.
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DOI：
10.1167/iovs.15-18513
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发表时间：
2016-03
影响因子：
4.4
通讯作者：
Trucco E
中科院分区：
文献类型：
--
作者：
Annunziata R;Kheirkhah A;Aggarwal S;Cavalcanti BM;Hamrah P;Trucco E
评估自动弯曲度估计和解释的新颖系统的性能。采用监督策略（由观察者评分驱动）来自动识别弯曲度测量的组合（即弯曲度表示），从而与观察者达成最佳一致性。我们研究了 18 种弯曲度测量值，包括在多个空间尺度上计算的曲率和拐点密度。为了利用曲折解释，我们提出了每个图像映射到的曲折平面（TP）。对 140 张中央角膜基底神经丛的图像进行了实验，涵盖四个弯曲程度。三名经验丰富的观察者独立对每幅图像进行评分。最佳的弯曲度表示是空间尺度 2 和 5 的平均曲率的组合。这些弯曲度测量是所提出的 TP（解释）的轴。弯曲度估计系统在全局和每个级别的基础上与观察者表现出强烈的一致性。与每个观察者的一致性（斯皮尔曼相关性）具有统计显着性（αs = 0.05，P < 0.0001），并且在三分之二的情况下高于至少一名其他观察者的一致性（ρOUR = 0.7594 对比 ρObs3 = 0.7225；ρOUR = 0.8880 对比 ρObs1 = 0.8017，ρObs3 = 0.7315）。根据配对样本 t 检验，这些改进是显着的 (P < 0.001)。我们的自动化系统通过四个弯曲度级别（离散比例）对图像进行分层，匹配或超过经验丰富的观察者的准确性。重要的是，TP 允许在二维连续尺度上评估弯曲度，从而更好地区分图像。
To assess the performance of a novel system for automated tortuosity estimation and interpretation. A supervised strategy (driven by observers' grading) was employed to automatically identify the combination of tortuosity measures (i.e., tortuosity representation) leading to the best agreement with the observers. We investigated 18 tortuosity measures including curvature and density of inflection points, computed at multiple spatial scales. To leverage tortuosity interpretation, we propose the tortuosity plane (TP) onto which each image is mapped. Experiments were carried out on 140 images of subbasal nerve plexus of the central cornea, covering four levels of tortuosity. Three experienced observers graded each image independently. The best tortuosity representation was the combination of mean curvature at spatial scales 2 and 5. These tortuosity measures were the axes of the proposed TP (interpretation). The system for tortuosity estimation revealed strong agreement with the observers on a global and per-level basis. The agreement with each observer (Spearman's correlation) was statistically significant (αs = 0.05, P < 0.0001) and higher than that of at least one of the other observers in two out of three cases (ρOUR = 0.7594 versus ρObs3 = 0.7225; ρOUR = 0.8880 versus ρObs1 = 0.8017, ρObs3 = 0.7315). Based on paired-sample t-tests, these improvements were significant (P < 0.001). Our automated system stratifies images by four tortuosity levels (discrete scale) matching or exceeding the accuracy of experienced observers. Of importance, the TP allows the assessment of tortuosity on a two-dimensional continuous scale, thus leading to a finer discrimination among images.