Images accompanying the paper "Enabling high-throughput quantitative wood anatomy through a dedicated pipeline"
(2025)
- Author
- Jan Van den Bulcke (UGent) , Ruben De Blaere (UGent) and Louis Verschuren (UGent)
- Organization
- Project
-
- SmartWoodID: Smart classification of Congolese timbers: deep learning techniques for enforcing forest conservation
- A game-changing perspective on intra-seasonal wood formation dynamics using high-resolution X-ray Computed Tomography to elucidate leaf senescence and autumn dynamics of temperate deciduous trees in Europe
- ACcurate Temperature REconstructions and climate change mapping in tree rings of Ancient bristlecone pines, the Longest-living trees in the world [ACTREAL]
- An X-ray view on the intra-seasonal dynamics of carbon storage in trees [XINCAST]
- Abstract
- Images of increment cores acquired with the Gigapixel Woodbot. Software for building your own Gigapixel Woodbot can be found on https://doi.org/10.5281/zenodo.14637832. Releases of software for analysis of the images can be found on https://doi.org/10.5281/zenodo.14637855. The training datasets and trained YOLOv8 model needed to run the analysis, can be found on https://doi.org/10.5281/zenodo.14604996. The full images of the disks (see paper for more details) can be found on https://doi.org/10.6019/S-BIAD1574. This is part of an entire sample preparation, imaging and analysis pipeline available in the paper "Enabling high-throughput quantitative wood anatomy through a dedicated pipeline" by Van den Bulcke and co-authors: https://doi.org/10.1186/s13007-025-01330-7. Cite our paper when using these data.
- Keywords
- wood anatomy, gigapixel imaging, deep learning
- License
- CC-BY-4.0
- Access
- open access
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JKAJ2PHB0JGY3YZQN1HVGY2N
@misc{01JKAJ2PHB0JGY3YZQN1HVGY2N,
abstract = {{Images of increment cores acquired with the Gigapixel Woodbot.
Software for building your own Gigapixel Woodbot can be found on https://doi.org/10.5281/zenodo.14637832.
Releases of software for analysis of the images can be found on https://doi.org/10.5281/zenodo.14637855.
The training datasets and trained YOLOv8 model needed to run the analysis, can be found on https://doi.org/10.5281/zenodo.14604996.
The full images of the disks (see paper for more details) can be found on https://doi.org/10.6019/S-BIAD1574.
This is part of an entire sample preparation, imaging and analysis pipeline available in the paper "Enabling high-throughput quantitative wood anatomy through a dedicated pipeline" by Van den Bulcke and co-authors: https://doi.org/10.1186/s13007-025-01330-7.
Cite our paper when using these data.}},
author = {{Van den Bulcke, Jan and De Blaere, Ruben and Verschuren, Louis}},
keywords = {{wood anatomy,gigapixel imaging,deep learning}},
publisher = {{Zenodo}},
title = {{Images accompanying the paper "Enabling high-throughput quantitative wood anatomy through a dedicated pipeline"}},
url = {{http://doi.org/10.5281/ZENODO.14627908}},
year = {{2025}},
}
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