Novel approach for anterior chamber angle analysis - Anterior chamber angle detection with edge measurement and identification algorithm (ACADEMIA)
Novel approach for anterior chamber angle analysis - Anterior chamber angle detection with edge measurement and identification algorithm (ACADEMIA)
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DOI：
10.1001/archopht.124.10.1395
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发表时间：
2006-10-01
影响因子：
--
通讯作者：
Lam, Dennis Shun-chiu
中科院分区：
文献类型：
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作者：
Leung, Christopher Kai-shun;Yung, Wing-ho;Lam, Dennis Shun-chiu
目的：描述一种测量前房角尺寸和配置的新方法。方法：从超声生物显微镜图像数据库中随机选择 69 张图像来开发算法。选择三十幅图像进行进一步分析。将8位灰度超声生物显微镜图像的每个像素的值量化为0（黑色）或1（白色），检测勾画角度的边缘点并用直线拟合。然后测量前房角的尺寸和轮廓。结果：由于强背景噪声，算法未能正确识别 69 幅图像中的 8 幅（11.6%）边缘点。根据导出的角度轮廓确定了三种基本类型的角度配置：恒定、增加和减少，分别对应于平坦、向前弯曲和向后弯曲的虹膜轮廓。角度测量显示与小梁-虹膜角度和角度张开距离500（计算为从角膜内皮到垂直于距巩膜骨刺500μm处绘制的线的前虹膜表面的距离）高度相关。在从角度轮廓导出的平均角度与角度张开距离 500 (r = 0.91) 之间发现最强的关联。结论：所提出的算法与角度张开距离和小梁虹膜角度具有高度相关性，并具有完全自动化、可重复性和能够捕获特征角度配置的附加优点。然而，需要具有高信噪比的高质量超声生物显微镜图像才能正确识别边缘点。
Objective: To describe a novel approach to measuring anterior chamber angle dimensions and configurations.Methods: Sixty-nine images were selected randomly from the ultrasound biomicroscopic image database to develop the algorithm. Thirty images were selected for further analyses. The value of each pixel of the 8-bit grayscale ultrasound biomicroscopic images was quantized into 0 (black) or 1 (white), and the edge points outlining the angle were detected and fitted with straight lines. The dimensions and profiles of anterior chamber angles were then measured.Results: The algorithm failed to identify the edge points correctly in 8 (11.6%) of 69 images because of strong background noise. Three basic types of angle configuration were identified based on the derived angle profiles: constant, increasing, and decreasing, which corresponded to flat, bowed forward, and bowed backward iris contours, respectively. The angle measurements demonstrated high correlation with trabecular-iris angle and angle opening distance 500 (calculated as the distance from the corneal endothelium to the anterior iris surface perpendicular to a line drawn at 500 mu m from the scleral spur). The strongest association was found between the averaged angle derived from the angle profile and the angle opening distance 500 (r = 0.91).Conclusion: The proposed algorithm has high correlations with angle opening distance and trabecular-iris angle with the added advantages of being fully automated, reproducible, and able to capture the characteristic angle configurations. However, good-quality ultrasound biomicroscopic images with high signal-to-noise ratio are required to identify the edge points correctly.