Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets
Segmenting Root Systems in X-Ray Computed Tomography Images Using Level Sets
复制标题
DOI：
10.1109/wacv.2018.00070
复制
发表时间：
2018-03
期刊：
影响因子：
--
通讯作者：
A. Tabb;K. Duncan;C. Topp
中科院分区：
文献类型：
--
作者：
A. Tabb;K. Duncan;C. Topp
为了在不挖掘的情况下有效地研究植物的根系结构，需要在X射线计算机断层扫描图像中从土壤和其他生长介质中分割出植物根。然而，在这种情况下，分割是一个具有挑战性的问题，因为根区域和非根区域共享相似的特征。在本文中，我们描述了一种基于水平集的方法，该方法特别适用于这种分割问题。特别是，我们解决了在大图像体上使用水平集方法进行根部分割的问题，并使用占用网格跟踪前方的活动区域。这种方法允许对窄带算法进行直接的修改，从而可以避免过度的前移和后移，通过修改Meijster等人的S距离变换算法，可以在线性时间内完成窄带背景下的距离图计算，并且迭代地使用图像体积的区域来估计根类和非根类的分布。给出了生长在三种不同介质中的三种不同成熟度的植物的结果。与最先进的X光CT图像体根分割方法相比，我们的方法是有利的。
The segmentation of plant roots from soil and other growing media in X-ray computed tomography images is needed to effectively study the root system architecture without excavation. However, segmentation is a challenging problem in this context because the root and non-root regions share similar features. In this paper, we describe a method based on level sets and specifically adapted for this segmentation problem. In particular, we deal with the issues of using a level sets approach on large image volumes for root segmentation, and track active regions of the front using an occupancy grid. This method allows for straightforward modifications to a narrow-band algorithm such that excessive forward and backward movements of the front can be avoided, distance map computations in a narrow band context can be done in linear time through modification of Meijster et al.'s distance transform algorithm, and regions of the image volume are iteratively used to estimate distributions for root versus non-root classes. Results are shown of three plant species of different maturity levels, grown in three different media. Our method compares favorably to a state-of-the-art method for root segmentation in X-ray CT image volumes.