ArticleFrontiers in zoology2015
Performance of single and multi-atlas based automated landmarking methods compared to expert annotations in volumetric microCT datasets of mouse mandibles.
Article in Frontiers in zoology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Development of an automated landmarking tool for the femur in dual-energy X-ray absorptiometry scans using contour-based image analysis.JBMR plus · 2026Article
- Assessing the application of landmark-free morphometrics to macroevolutionary analyses.BMC ecology and evolution · 2025Article
- Opportunities and Challenges in Applying AI to Evolutionary Morphology.Integrative organismal biology (Oxford, England) · 2024Review
- Automated landmarking via multiple templates.PloS one · 2022Article
- ALPACA: A fast and accurate computer vision approach for automated landmarking of three-dimensional biological structures.Methods in ecology and evolution · 2021Article
- SlicerMorph: An open and extensible platform to retrieve, visualize and analyze 3D morphology.Methods in ecology and evolution · 2021Article
- Landmark-free, parametric hypothesis tests regarding two-dimensional contour shapes using coherent point drift registration and statistical parametric mapping.PeerJ. Computer science · 2021Article
- A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics.Evolutionary biology · 2020Article
- The effect of automated landmark identification on morphometric analyses.Journal of anatomy · 2019Article
- Mouse Skull Mean Shape and Shape Robustness Rely on Different Genetic Architectures and Different Loci.Frontiers in genetics · 2019Article
- A population level atlas of Mus musculus craniofacial skeleton and automated image-based shape analysis.Journal of anatomy · 2017Article
- Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old.Human brain mapping · 2017Article
- Does 3D Phenotyping Yield Substantial Insights in the Genetics of the Mouse Mandible Shape?G3 (Bethesda, Md.) · 2016Article
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
Abstract
backgroundHere we present an application of advanced registration and atlas building framework DRAMMS to the automated annotation of mouse mandibles through a series of tests using single and multi-atlas segmentation paradigms and compare the outcomes to the current gold standard, manual annotation.
resultsOur results showed multi-atlas annotation procedure yields landmark precisions within the human observer error range. The mean shape estimates from gold standard and multi-atlas annotation procedure were statistically indistinguishable for both Euclidean Distance Matrix Analysis (mean form matrix) and Generalized Procrustes Analysis (Goodall F-test). Further research needs to be done to validate the consistency of variance-covariance matrix estimates from both methods with larger sample sizes.
conclusionMulti-atlas annotation procedure shows promise as a framework to facilitate truly high-throughput phenomic analyses by channeling investigators efforts to annotate only a small portion of their datasets.
Indexed as
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.