1 research outputs found
Segmenting root systems in X-ray computed tomography images using level sets
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.Comment: 11 page