Automated Measurement of the Arteriolar-to-Venular Width Ratio in Digital Color Fundus Photographs
Automated Measurement of the Arteriolar-to-Venular Width Ratio in Digital Color Fundus Photographs
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DOI：
10.1109/tmi.2011.2159619
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发表时间：
2011-11-01
影响因子：
10.6
通讯作者：
Abramoff, Michael D.
中科院分区：
文献类型：
--
作者：
Niemeijer, Meindert;Xu, Xiayu;Abramoff, Michael D.
视网膜动脉与静脉的宽度比[小动脉与小静脉直径比（AVR）]降低，已被公认为成人脑萎缩、中风和其他心血管事件的预测指标。动脉和静脉迂曲和扩张以及AVR降低也是早产儿视网膜病变的标志。这项工作提出了一种自动化的方法来估计的AVR在视网膜彩色图像检测的视盘的位置，确定一个适当的区域的兴趣（ROI），分类血管动脉或静脉，估计血管宽度，并计算AVR。在血管分割和血管宽度确定之后，定位视盘，并且系统消除AVR测量ROI之外的所有血管。对剩余的血管应用去中心化操作，之后去除血管交叉点和分叉点，留下仅由血管中心线像素组成的一组血管段。从每个中心线像素中提取特征，以便为这些像素分配指示像素是静脉的一部分的可能性的软标签。由于已连接血管段中的所有中心线像素应是相同类型，因此将中值软标签分配给该段中的每个中心线像素。接下来，使用迭代算法匹配动脉静脉对，并且使用血管的宽度来计算AVR。我们在一组65张高分辨率数字彩色眼底照片上训练和测试了该算法，使用参考标准指示图像中的每个主要血管是动脉还是静脉。我们比较了我们的系统产生的AVR值与半自动参考系统确定的值。我们在40幅图像中获得了平均无符号误差0.06（SD 0.04），平均AVR为0.67。使用半自动系统的第二名观察者在该组图像上获得了相同的平均无符号误差0.06（SD 0.05），平均AVR为0.66。本研究中使用的检测数据和参比标准品已公开提供。
A decreased ratio of the width of retinal arteries to veins [arteriolar-to-venular diameter ratio (AVR)], is well established as predictive of cerebral atrophy, stroke and other cardiovascular events in adults. Tortuous and dilated arteries and veins, as well as decreased AVR are also markers for plus disease in retinopathy of prematurity. This work presents an automated method to estimate the AVR in retinal color images by detecting the location of the optic disc, determining an appropriate region of interest (ROI), classifying vessels as arteries or veins, estimating vessel widths, and calculating the AVR. After vessel segmentation and vessel width determination, the optic disc is located and the system eliminates all vessels outside the AVR measurement ROI. A skeletonization operation is applied to the remaining vessels after which vessel crossings and bifurcation points are removed, leaving a set of vessel segments consisting of only vessel centerline pixels. Features are extracted from each centerline pixel in order to assign these a soft label indicating the likelihood that the pixel is part of a vein. As all centerline pixels in a connected vessel segment should be the same type, the median soft label is assigned to each centerline pixel in the segment. Next, artery vein pairs are matched using an iterative algorithm, and the widths of the vessels are used to calculate the AVR. We trained and tested the algorithm on a set of 65 high resolution digital color fundus photographs using a reference standard that indicates for each major vessel in the image whether it is an artery or vein. We compared the AVR values produced by our system with those determined by a semi-automated reference system. We obtained a mean unsigned error of 0.06 (SD 0.04) in 40 images with a mean AVR of 0.67. A second observer using the semi-automated system obtained the same mean unsigned error of 0.06 (SD 0.05) on the set of images with a mean AVR of 0.66. The testing data and reference standard used in this study has been made publicly available.