Dept. of Electr. Eng., Ohio State Univ., Columbus, OH.
IEEE Trans Med Imaging. 1991;10(2):109-21. doi: 10.1109/42.79468.
An algorithm for computationally focusing the tissue boundaries detected from magnetic resonance images is presented. The proposed approach is a novel, whole-contour-based technique for tracing edges selected at a coarse scale into successively finer scales to recover the needed precision. The tracing algorithm builds consensus through a fast pixel voting scheme. Also presented is a rigorous method for determining the appropriate itinerary when traversing scale space, beginning from the premise of a maximum pixel migration per unit change in scale parameter. This leads to an efficient method of processing images so as to maximize accuracy and minimize noise. Although the LoG (Laplacian of Gaussian) is used for many of the experiments, results using a novel edge detector which is mathematically superior to and faster to compute than the LoG and for which fewer steps are required to traverse the same effective span in scale space are presented. Experimental results on real data are presented, and other potential applications are discussed.
提出了一种从磁共振图像中计算聚焦组织边界的算法。所提出的方法是一种新颖的、基于整体轮廓的技术，用于将在粗尺度上选择的边缘跟踪到逐渐更细的尺度，以恢复所需的精度。跟踪算法通过快速像素投票方案建立共识。还提出了一种严格的方法来确定在尺度空间中遍历的适当行程，从每单位尺度参数变化的最大像素迁移的前提开始。这导致了一种有效的图像处理方法，以最大限度地提高准确性和最小化噪声。尽管在许多实验中使用了 LoG（高斯拉普拉斯算子），但也提出了使用一种新的边缘检测器的结果，该边缘检测器在数学上优于 LoG，并且计算速度更快，并且在尺度空间中遍历相同有效跨度所需的步骤更少。给出了真实数据的实验结果，并讨论了其他潜在的应用。
