TTGS: A topology-preserving method for vector reconstruction of plant cell wall networks
- 1College of Engineering, South China Agricultural University, Guangzhou, China
- 2Guangdong Province Agricultural Technology Extension Center, Guangzhou, China
- 3College of Information Engineering, Northwest A&F University, Yangling, China
Abstract
Plant cell wall architecture influences tissue mechanics and transport, but converting microscopy-derived masks into finite-element geometries requires both accurate centerline localization and preservation of network topology. We developed a topology-preserving thinning-based graph skeletonization method (TTGS) that converts binary cell wall masks into vectorizable node-edge graphs through skeleton extraction, node-cluster identification, path tracing, and connectivity-preserving linearization. Seven reconstruction methods were evaluated using the same binary masks from 12 cross-sectional micrographs of sugarcane (Saccharum officinarum L.) parenchyma, vascular bundles, and roots. Across all images, TTGS achieved a structure completeness of 44.04 ± 12.98%, a mean geometric deviation of 2.93 ± 1.04 px, a valid skeleton ratio of 94.49 ± 3.71%, and a breakage rate of 0%. Its unmatched internal endpoint count was 5.00 ± 5.38, while its closed-contour F1 and degree-aware junction F1 reached 93.73 ± 5.56% and 92.75 ± 3.54%, respectively. Among the methods satisfying the predefined short-fragment criterion, TTGS achieved the highest structure completeness and valid skeleton ratio and the lowest geometric deviation. A representative TTGS vector network was imported into finite-element software, reconstructed as a three-dimensional cell-scale model, and successfully solved to obtain a continuous stress distribution. These results show that TTGS balances geometric fidelity with topology preservation and supports the workflow from microscopy-derived masks to vector reconstruction and finite-element analysis.
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BibTeX
@article{wang2026ttgs,
title = {{TTGS: A topology-preserving method for vector reconstruction of plant cell wall networks}},
author = {Zaibin Wang and Qingting Liu and Tao Wu and Jiaoli Jiang and Yan Zhang and Xueting Han and Xiaojuan Lin and Qing Zhou and Zhenghe Luo},
journal = {Plant Phenomics},
year = {2026},
month = oct,
doi = {10.1016/j.plaphe.2026.100294},
url = {https://doi.org/10.1016/j.plaphe.2026.100294},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - TTGS: A topology-preserving method for vector reconstruction of plant cell wall networks
AU - Zaibin Wang
AU - Qingting Liu
AU - Tao Wu
AU - Jiaoli Jiang
AU - Yan Zhang
AU - Xueting Han
AU - Xiaojuan Lin
AU - Qing Zhou
AU - Zhenghe Luo
PY - 2026
DA - 2026/10/12
JO - Plant Phenomics
DO - 10.1016/j.plaphe.2026.100294
UR - https://doi.org/10.1016/j.plaphe.2026.100294
AB - Plant cell wall architecture influences tissue mechanics and transport, but converting microscopy-derived masks into finite-element geometries requires both accurate centerline localization and preservation of network topology. We developed a topology-preserving thinning-based graph skeletonization method (TTGS) that converts binary cell wall masks into vectorizable node-edge graphs through skeleton extraction, node-cluster identification, path tracing, and connectivity-preserving linearization. Seven reconstruction methods were evaluated using the same binary masks from 12 cross-sectional micrographs of sugarcane (Saccharum officinarum L.) parenchyma, vascular bundles, and roots. Across all images, TTGS achieved a structure completeness of 44.04 ± 12.98%, a mean geometric deviation of 2.93 ± 1.04 px, a valid skeleton ratio of 94.49 ± 3.71%, and a breakage rate of 0%. Its unmatched internal endpoint count was 5.00 ± 5.38, while its closed-contour F1 and degree-aware junction F1 reached 93.73 ± 5.56% and 92.75 ± 3.54%, respectively. Among the methods satisfying the predefined short-fragment criterion, TTGS achieved the highest structure completeness and valid skeleton ratio and the lowest geometric deviation. A representative TTGS vector network was imported into finite-element software, reconstructed as a three-dimensional cell-scale model, and successfully solved to obtain a continuous stress distribution. These results show that TTGS balances geometric fidelity with topology preservation and supports the workflow from microscopy-derived masks to vector reconstruction and finite-element analysis.
SN - 2643-6515
ER -