Orthogonal moments for determining correspondence between vessel bifurcations for retinal image registration
Orthogonal moments for determining correspondence between vessel bifurcations for retinal image registration
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DOI：
10.1016/j.cmpb.2015.02.009
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发表时间：
2015-05-01
影响因子：
6.1
通讯作者：
Kulkarni, Jayant V.
中科院分区：
文献类型：
--
作者：
Patankar, Sanika S.;Kulkarni, Jayant V.
糖尿病视网膜病变是致盲的主要原因之一，视网膜图像配准是诊断和监测糖尿病视网膜病变的必要步骤。长期糖尿病会影响视网膜血管和毛细血管，最终导致失明。这种对视网膜的进行性损害和随后的失明可以通过定期视网膜筛查来预防。可以通过比较定期视网膜筛查期间捕获的视网膜图像来评估DR造成的损伤程度。在周期性筛选时的图像采集过程中，在视网膜图像中引入了平移、旋转和缩放（TRS）。因此，视网膜图像配准是视网膜视网膜病变筛查、诊断、治疗和评估自动化系统的重要步骤。本文提出了一种用正交矩不变量作为特征来确定参考和测试视网膜图像中优势点（血管分支）之间的对应关系的视网膜图像配准算法。由于正交矩对TRS是不变的；由于TRS，血管分叉周围的矩不变特征没有改变，可以用来确定参考和测试视网膜图像之间的对应关系。血管分叉点被定位在分割、细化（单像素血管宽度）的视网膜图像中，并在相应的灰度视网膜图像中进行标记。基于不变矩特征，建立了参考图像和测试图像血管分叉的对应关系。进一步利用相似变换估计了测试视网膜图像相对于参考视网膜图像的TRS。利用估计的配准参数将测试视网膜图像与参考视网膜图像对齐。用标记血管分叉点的平均误差和标准差来评价配准的准确性。实验在DRIVE数据库、STARE数据库、VARIA数据库和印度浦那地方政府医院提供的数据库上进行。实验结果表明了该算法对视网膜图像配准的有效性。2015爱思唯尔爱尔兰有限公司版权所有。
Retinal image registration is a necessary step in diagnosis and monitoring of Diabetes Retinopathy (DR), which is one of the leading causes of blindness. Long term diabetes affects the retinal blood vessels and capillaries eventually causing blindness. This progressive damage to retina and subsequent blindness can be prevented by periodic retinal screening. The extent of damage caused by DR can be assessed by comparing retinal images captured during periodic retinal screenings. During image acquisition at the time of periodic screenings translation, rotation and scale (TRS) are introduced in the retinal images. Therefore retinal image registration is an essential step in automated system for screening, diagnosis, treatment and evaluation of DR. This paper presents an algorithm for registration of retinal images using orthogonal moment invariants as features for determining the correspondence between the dominant points (vessel bifurcations) in the reference and test retinal images. As orthogonal moments are invariant to TRS; moment invariants features around a vessel bifurcation are unaltered due to TRS and can be used to determine the correspondence between reference and test retinal images. The vessel bifurcation points are located in segmented, thinned (mono pixel vessel width) retinal images and labeled in corresponding grayscale retinal images. The correspondence between vessel bifurcations in reference and test retinal image is established based on moment invariants features. Further the TRS in test retinal image with respect to reference retinal image is estimated using similarity transformation. The test retinal image is aligned with reference retinal image using the estimated registration parameters. The accuracy of registration is evaluated in terms of mean error and standard deviation of the labeled vessel bifurcation points in the aligned images. The experimentation is carried out on DRIVE database, STARE database, VARIA database and database provided by local government hospital in Pune, India. The experimental results exhibit effectiveness of the proposed algorithm for registration of retinal images. (C) 2015 Elsevier Ireland Ltd. All rights reserved.