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Frame-rate spatial referencing based on invariant indexing and alignment with application to online retinal image registration

机译:基于不变索引和对齐的帧率空间参考及其在在线视网膜图像配准中的应用

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This paper describes an algorithm to continually and accurately estimate the absolute location of a diagnostic or surgical tool (such as a laser) pointed at the human retina, from a series of image frames. We treat the problem as a registration problem using diagnostic images to build a spatial map of the retina and then registering each online image against this map. Since the image location where the laser strikes the retina is easily found, this registration determines the position of the laser in the global coordinate system defined by the spatial map. For each online image, the algorithm computes similarity invariants, locally valid despite the curved nature of the retina, from constellations of vascular landmarks. These are detected using a high-speed algorithm that iteratively traces the blood vessel structure. Invariant indexing establishes initial correspondences between landmarks from the online image and landmarks stored in the spatial map. Robust alignment and verification steps extend the similarity transformation computed from these initial correspondences to a global, high-order transformation. In initial experimentation, the method has achieved 100 percent success on 1024 /spl times/ 1024 retina images. With a version of the tracing algorithm optimized for speed on 512 /spl times/ 512 images, the computation time is only 51 milliseconds per image on a 900MHz PentiumIII processor and a 97 percent success rate is achieved. The median registration error in either case is about 1 pixel.
机译:本文介绍了一种算法,该算法可以从一系列图像帧中连续准确地估计出指向人体视网膜的诊断或外科手术工具(例如激光)的绝对位置。我们使用诊断图像将问题视为配准问题,以构建视网膜的空间图,然后根据该图配准每个在线图像。由于很容易找到激光撞击视网膜的图像位置,因此该配准确定了激光在由空间图定义的全局坐标系中的位置。对于每个在线图像,该算法都会根据血管界标的星座图来计算相似不变性,尽管视网膜具有弯曲性质,但在局部有效。使用高速跟踪血管结构的算法检测这些。不变索引建立了在线图像中的地标与存储在空间地图中的地标之间的初始对应关系。稳健的对齐和验证步骤将根据这些初始对应关系计算出的相似度转换扩展为全局的高阶转换。在最初的实验中,该方法在1024张/ spl次/ 1024张视网膜图像上已取得100%的成功。使用针对512个/ spl次/ 512张图像进行速度优化的跟踪算法版本,在900MHz PentiumIII处理器上,每张图像的计算时间仅为51毫秒,并且成功率为97%。在任何一种情况下,中值配准误差约为1个像素。

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