使用快速行进算法对分割后的医学图像进行拓扑校正。
Topology correction of segmented medical images using a fast marching algorithm.
作者信息
Bazin Pierre-Louis, Pham Dzung L
机构信息
Laboratory of Medical Image Computing, Neuroradiology Division, Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21218, USA.
出版信息
Comput Methods Programs Biomed. 2007 Nov;88(2):182-90. doi: 10.1016/j.cmpb.2007.08.006. Epub 2007 Oct 17.
Abstract
We present here a new method for correcting the topology of objects segmented from medical images. Whereas previous techniques alter a surface obtained from a binary segmentation of the object, our technique can be applied directly to the image intensities of a probabilistic or fuzzy segmentation, thereby propagating the topology for all isosurfaces of the object. From an analysis of topological changes and critical points in implicit surfaces, we derive a topology propagation algorithm that enforces any desired topology using a fast marching technique. The method has been applied successfully to the correction of the cortical gray matter/white matter interface in segmented brain images and is publicly released as a software plug-in for the MIPAV package.
摘要
我们在此展示一种用于校正从医学图像中分割出的物体拓扑结构的新方法。以往的技术是改变从物体的二值分割得到的表面，而我们的技术可以直接应用于概率性或模糊分割的图像强度，从而为物体的所有等值面传播拓扑结构。通过对隐式曲面中的拓扑变化和临界点进行分析，我们推导出一种拓扑传播算法，该算法使用快速行进技术来强制实现任何所需的拓扑结构。该方法已成功应用于校正分割后的脑图像中的皮质灰质/白质界面，并作为MIPAV软件包的一个软件插件公开发布。
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