ArticleIntegrative organismal biology (Oxford, England)2023
An Open-Source Photogrammetry Workflow for Reconstructing 3D Models.
Article in Integrative organismal biology (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- From 3D Surface Documentation to Visualization in Forensic Practice: A Review of Current Methods and Emerging Technologies.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2026Review
- MorphoCloud: Democratizing Access to High-Performance Computing for Morphological Data Analysis.F1000Research · 2026Article
- MorphoCloud: Democratizing Access to High-Performance Computing for Morphological Data Analysis.ArXiv · 2025Article
- SlicerMorph photogrammetry: an open-source photogrammetry workflow for reconstructing 3D models.Biology open · 2025Article
- BFEX: A Toolbox for Finite Element Analysis With Fossils and Blender.Ecology and evolution · 2025Article
- Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting.Journal of imaging · 2025Article
- Article
- Applying 3D Models of Giant Salamanders to Explore Form-Function Relationships in Early Digit-Bearing Tetrapods.Integrative and comparative biology · 2024Article
- Phylogenetic structure of body shape in a diverse inland ichthyofauna.Scientific reports · 2023Article
- Tooth shape asymmetry in post-canine dentition: Evidence-based morphometric insights.Journal of oral biology and craniofacial researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acquiring accurate 3D biological models efficiently and economically is important for morphological data collection and analysis in organismal biology. In recent years, structure-from-motion (SFM) photogrammetry has become increasingly popular in biological research due to its flexibility and being relatively low cost. SFM photogrammetry registers 2D images for reconstructing camera positions as the basis for 3D modeling and texturing. However, most studies of organismal biology still relied on commercial software to reconstruct the 3D model from photographs, which impeded the adoption of this workflow in our field due the blocking issues such as cost and affordability. Also, prior investigations in photogrammetry did not sufficiently assess the geometric accuracy of the models reconstructed. Consequently, this study has two goals. First, we presented an affordable and highly flexible SFM photogrammetry pipeline based on the open-source package OpenDroneMap (ODM) and its user interface WebODM. Second, we assessed the geometric accuracy of the photogrammetric models acquired from the ODM pipeline by comparing them to the models acquired via microCT scanning, the de facto method to image skeleton. Our sample comprised 15
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.