Martinez-Perez M Elena, Espinosa-Romero Arturo
Department of Computer Science, Institute of Research in Applied Mathematics and Systems, UNAM, DF, México.
Opt Express. 2012 May 7;20(10):11451-65. doi: 10.1364/OE.20.011451.
We present a 3D reconstruction of retinal blood vessel trees using two views of fundus images. The problem is addressed by using well known computer vision techniques which consider: 1) The recovery of camera-eyeball model parameters by an auto-calibration method. The camera parameters are found via the solution of simplified Kruppa equations, based on correspondences found by a LMedS optimisation correlation between pairs of eight different views. 2) The extraction of blood vessels and skeletons from two fundus images. 3) The matching of corresponding points of the two skeleton trees. The trees are previously labelled during the analysis of 2D binary images. Finally, 4) the lineal triangulation of matched correspondence points and the surface modelling via generalised cylinders using diameter measurements extracted from the 2D binary images. The method is nearly automatic and it is tested with 2 sets of 10 fundus retinal images, each one taken from different subjects. Results of 3D vein and artery trees reconstructions are shown.
我们使用眼底图像的两个视图展示了视网膜血管树的三维重建。该问题通过使用著名的计算机视觉技术来解决，这些技术考虑：1）通过自动校准方法恢复相机 - 眼球模型参数。相机参数通过求解简化的克鲁帕方程来找到，该方程基于通过LMedS优化相关性在八对不同视图之间找到的对应关系。2）从两个眼底图像中提取血管和骨架。3）两个骨架树对应点的匹配。这些树在二维二值图像分析期间预先标记。最后，4）匹配对应点的线性三角测量以及使用从二维二值图像中提取的直径测量值通过广义圆柱体进行表面建模。该方法几乎是自动的，并且使用两组各10张眼底视网膜图像进行了测试，每组图像均取自不同的受试者。展示了三维静脉和动脉树重建的结果。
