Robust Skeletonization for Plant Root Structure Reconstruction from MRI

Abstract

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.

Plant phenotyping relevance

MRI画像から植物根系を再構成し、セグメンテーションと3D骨格化で根構造を抽出する手法の開発・専門家比較検証が中心であるため。

Code and data availability

The article describes a root skeletonization pipeline evaluated on 22 MRI scans with expert annotations and 3D U-Net segmentations, but no public dataset, code, model, or supplement availability is stated anywhere in the supplied blocks, and no author-provided URLs are present.

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