Laliberté France, Gagnon Langis, Sheng Yunlong
CRIM Montréal, QC H3A 1B9, Canada.
IEEE Trans Med Imaging. 2003 May;22(5):661-73. doi: 10.1109/TMI.2003.812263.
We present the results of a study on the application of registration and pixel-level fusion techniques to retinal images. The images are of different modalities (color, fluorescein angiogram), different resolutions, and taken at different times (from a few minutes during an angiography examination to several years between two examinations). We propose a new registration method based on global point mapping with blood vessel bifurcations as control points and a search for control point matches that uses local structural information of the retinal network. Three transformation types (similarity, affine, and second-order polynomial) are evaluated on each image pair. Fourteen pixel-level fusion techniques have been tested and classified according to their qualitative and quantitative performance. Four quantitative fusion performance criteria are used to evaluate the gain obtained with the grayscale fusion.
我们展示了一项关于将配准和像素级融合技术应用于视网膜图像的研究结果。这些图像具有不同的模态(彩色、荧光血管造影)、不同的分辨率,并且拍摄时间不同(从血管造影检查期间的几分钟到两次检查之间的数年)。我们提出了一种基于全局点映射的新配准方法,该方法以血管分叉作为控制点,并利用视网膜网络的局部结构信息来搜索控制点匹配。对每对图像评估了三种变换类型(相似性、仿射和二阶多项式)。已经测试了十四种像素级融合技术,并根据它们的定性和定量性能进行了分类。使用四个定量融合性能标准来评估灰度融合所获得的增益。