ArticleBMC evolutionary biology2018
Alpha shapes: determining 3D shape complexity across morphologically diverse structures.
Article in BMC evolutionary biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed.
- New perspectives on head and neck allometry and ecomorphology in tetrapods.Biological reviews of the Cambridge Philosophical Society · 2026Review
- A suture in time: The ontogeny of cranial suture morphology in mammals.Journal of anatomy · 2026Article
- Commentary: The missing sabertooth baculum-At what point might the absence of evidence reasonably be considered evidence of absence?Anatomical record (Hoboken, N.J. : 2007) · 2025Article
- Determining the atlas correspondence of Desikan-Killiany-Tourville and Glasser MMP1 atlases across magnetic field strengths.Journal of neuroscience methods · 2025Article
- Quantifying the configurational complexity of biological systems in multivariate 'complexity space'.Journal of the Royal Society, Interface · 2025Article
- Morphological diversity in the honeyeater hyolingual apparatus and its relationship with nectarivory.PloS one · 2025Article
- Exploiting 2D Neural Network Frameworks for 3D Segmentation Through Depth Map Analytics of Harvested Wild Blueberries (Journal of imaging · 2024Article
- Automatic analysis of the continuous edges of stone tools reveals fundamental handaxe variability.Scientific reports · 2024Article
- Generative modeling of biological shapes and images using a probabilisticbioRxiv : the preprint server for biology · 2024Article
- 3D deconvolution of human skin immune architecture with Multiplex Annotated Tissue Imaging System.Science advances · 2023Article
- Establishment and characterization of oviductal organoids from farm and companion animals†.Biology of reproduction · 2023Article
- Baculum shape complexity correlates to metrics of post-copulatory sexual selection in Musteloidea.Journal of morphology · 2023Article
- A reinterpretation of the gap fraction of tree crowns from the perspectives of computer graphics and porous media theory.Frontiers in plant science · 2023Article
- Fossil bacula of five species of Borophaginae (Family: Canidae): Implications for their reproductive biology.PloS one · 2023Article
- New Method for Rapid 3D Reconstruction of Semi-Transparent Underwater Animals and Structures.Integrative organismal biology (Oxford, England) · 2023Article
- Chromosome size matters: genome evolution in the cyperid clade.Annals of botany · 2022Article
- Cortical thickness systematically varies with curvature and depth in healthy human brains.Human brain mapping · 2022Article
- 3D Single Molecule Super-Resolution Microscopy of Whole Nuclear Lamina.Frontiers in chemistry · 2022Article
- Assessing the patterns and drivers of shape complexity in the amblypygid pedipalp.Ecology and evolution · 2021Article
- Analysis of EEG Data Using Complex Geometric Structurization.Neural computation · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundFollowing recent advances in bioimaging, high-resolution 3D models of biological structures are now generated rapidly and at low-cost. To use this data to address evolutionary and ecological questions, an array of tools has been developed to conduct shape analysis and quantify topographic complexity. Here we focus particularly on shape techniques applied to irregular-shaped objects lacking clear homologous landmarks, and propose a new 'alpha-shapes' method for quantifying 3D shape complexity.
methodsWe apply alpha-shapes to quantify shape complexity in the mammalian baculum as an example of a morphologically disparate structure. Micro- computed-tomography (μCT) scans of bacula were conducted. Bacula were binarised and converted into point clouds. Following application of a scaling factor to account for absolute size differences, a suite of alpha-shapes was fitted per specimen. An alpha shape is formed from a subcomplex of the Delaunay triangulation of a given set of points, and ranges in refinement from a very coarse mesh (approximating convex hulls) to a very fine fit. 'Optimal' alpha was defined as the refinement necessary in order for alpha-shape volume to equal CT voxel volume, and was taken as a metric of overall 'complexity'.
resultsOur results show that alpha-shapes can be used to quantify interspecific variation in shape 'complexity' within biological structures of disparate geometry. The 'stepped' nature of alpha curves is informative with regards to the contribution of specific morphological features to overall 'complexity'. Alpha-shapes agrees with other measures of complexity (dissection index, Dirichlet normal energy) in identifying ursid bacula as having low shape complexity. However, alpha-shapes estimates mustelid bacula as being most complex, contrasting with other shape metrics. 3D fractal dimension is identified as an inappropriate metric of complexity when applied to bacula.
conclusionsAlpha-shapes is used to calculate 'optimal' alpha refinement as a proxy for shape 'complexity' without identifying landmarks. The implementation of alpha-shapes is straightforward, and is automated to process large datasets quickly. We interpret alpha-shapes as being particularly sensitive to concavities in surface topology, potentially distinguishing it from other shape complexity metrics. Beyond genital shape, the alpha-shapes technique holds considerable promise for new applications across evolutionary, ecological and palaeoecological disciplines.
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.