Structural reconstruction of plant roots from MRI is challenging, because of low resolution and low signal-to-noise ratio of the 3D measurements which may lead to disconnectivities and wrongly connected roots. We propose a two-stage approach for this task. The first stage is based on semantic root vs. soil segmentation and finds lowest-cost paths from any root voxel to the shoot. The second stage takes the largest fully connected component generated in the first stage and uses 3D skeletonization to extract a graph structure. We evaluate our method on 22 MRI scans and compare to human expert reconstructions.
Cite
@article{arxiv.2010.14440,
title = {Robust Skeletonization for Plant Root Structure Reconstruction from MRI},
author = {Jannis Horn and Yi Zhao and Nils Wandel and Magdalena Landl and Andrea Schnepf and Sven Behnke},
journal= {arXiv preprint arXiv:2010.14440},
year = {2020}
}
Comments
Accepted final version. In 25th International Conference on Pattern Recognition (ICPR2020)