Heneghan Conor, Flynn John, O'Keefe Michael, Cahill Mark
Department of Electronic and Electrical Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
Med Image Anal. 2002 Dec;6(4):407-29. doi: 10.1016/s1361-8415(02)00058-0.
Many retinal diseases are characterised by changes to retinal vessels. For example, a common condition associated with retinopathy of prematurity (ROP) is so-called plus disease, characterised by increased vascular dilation and tortuosity. This paper presents a general technique for segmenting out vascular structures in retinal images, and characterising the segmented blood vessels. The segmentation technique consists of several steps. Morphological preprocessing is used to emphasise linear structures such as vessels. A second derivative operator is used to further emphasise thin vascular structures, and is followed by a final morphological filtering stage. Thresholding of this image is used to provide a segmented vascular mask. Skeletonisation of this mask allows identification of points in the image where vessels cross (bifurcations and crossing points) and allows the width and tortuosity of vessel segments to be calculated. The accuracy of the segmentation stage is quite dependent on the parameters used, particularly at the thresholding stage. However, reliable measurements of vessel width and tortuosity were shown using test images. Using these tools, a set of images drawn from 23 subjects being screened for the presence of threshold ROP disease is considered. Of these subjects, 11 subsequently required treatment for ROP, 9 had no evidence of ROP, and 3 had spontaneously regressed ROP. The average vessel width and tortuosity for the treated subjects was 96.8 microm and 1.125. The corresponding figures for the non-treated cohort were 86.4 microm and 1.097. These differences were statistically significant at the 99% and 95% significance level, respectively. Subjects who progressed to threshold disease during the course of screening showed an average increase in vessel width of 9.6 microm and in tortuosity of +0.008. Only the change in width was statistically significant. Applying a simple retrospective screening paradigm based solely on vessel width and tortuosity yields a screening test with a sensitivity and specificity of 82% and 75%. Factors confounding a more accurate test include poor image quality, inaccuracies in vessel segmentation, inaccuracies in measurement of vessel width and tortuosity, and limitations inherent in screening based solely on examination of the posterior pole.
许多视网膜疾病的特征是视网膜血管发生变化。例如,与早产儿视网膜病变(ROP)相关的一种常见病症是所谓的“plus病”,其特征是血管扩张和迂曲增加。本文提出了一种用于分割视网膜图像中血管结构并对分割出的血管进行特征描述的通用技术。分割技术包括几个步骤。形态学预处理用于强调血管等线性结构。二阶导数算子用于进一步强调细血管结构,随后是最终的形态学滤波阶段。对该图像进行阈值处理以提供分割的血管掩码。该掩码的骨架化允许识别图像中血管交叉的点(分叉点和交叉点),并允许计算血管段的宽度和迂曲度。分割阶段的准确性很大程度上取决于所使用的参数,特别是在阈值处理阶段。然而,使用测试图像显示了血管宽度和迂曲度的可靠测量结果。使用这些工具,考虑了一组从23名接受阈值ROP疾病筛查的受试者中获取的图像。在这些受试者中,11人随后需要接受ROP治疗,9人没有ROP证据,3人ROP已自发消退。接受治疗的受试者的平均血管宽度和迂曲度分别为96.8微米和1.125。未治疗队列的相应数字为86.4微米和1.097。这些差异在99%和95%的显著性水平上分别具有统计学意义。在筛查过程中进展为阈值疾病的受试者显示血管宽度平均增加9.6微米,迂曲度增加+0.008。只有宽度变化具有统计学意义。仅基于血管宽度和迂曲度应用简单的回顾性筛查范式产生的筛查测试的灵敏度和特异性分别为82%和75%。影响更准确测试的因素包括图像质量差、血管分割不准确、血管宽度和迂曲度测量不准确以及仅基于后极检查的筛查固有的局限性。