ArticleJournal of the Royal Society, Interface2020
Three-dimensional computation of fibre orientation, diameter and branching in segmented image stacks of fibrous networks.
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Reduced-order modeling of solute transport within physiologically realistic solid tumor microenvironment.Frontiers in pharmacology · 2026Article
- REDUCED-ORDER MODELING OF SOLUTE TRANSPORT WITHIN PHYSIOLOGICALLY REALISTIC SOLID TUMOR MICROENVIRONMENT.bioRxiv : the preprint server for biology · 2025Article
- Fascicular Elastin Impacts Tendon-Specific Ramp-to-Failure and Fatigue Mechanics.Journal of biomechanical engineering · 2025Article
- Mueller matrix analysis of a biologically sourced engineered tissue construct as polarimetric phantom.Journal of biomedical optics · 2024Article
- The importance of 3D fibre architecture in cancer and implications for biomaterial model design.Nature reviews. Cancer · 2024Review
- Development of a multiphase perfusion model for biomimetic reduced-order dense tumors.Experimental and computational multiphase flow · 2023Article
- A Nonparametric Approach for Estimating Three-Dimensional Fiber Orientation Distribution Functions (ODFs) in Fibrous Materials.IEEE transactions on medical imaging · 2022Article
- Navigating the Collagen Jungle: The Biomedical Potential of Fiber Organization in Cancer.Bioengineering (Basel, Switzerland) · 2021Review
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
Fibre topography of the extracellular matrix governs local mechanical properties and cellular behaviour including migration and gene expression. While quantifying properties of the fibrous network provides valuable data that could be used across a breadth of biomedical disciplines, most available techniques are limited to two dimensions and, therefore, do not fully capture the architecture of three-dimensional (3D) tissue. The currently available 3D techniques have limited accuracy and applicability and many are restricted to a specific imaging modality. To address this need, we developed a novel fibre analysis algorithm capable of determining fibre orientation, fibre diameter and fibre branching on a voxel-wise basis in image stacks with distinct fibre populations. The accuracy of the technique is demonstrated on computer-generated phantom image stacks spanning a range of features and complexities, as well as on two-photon microscopy image stacks of elastic fibres in bovine tendon and dermis. Additionally, we propose a measure of axial spherical variance which can be used to define the degree of fibre alignment in a distribution of 3D orientations. This method provides a useful tool to quantify orientation distributions and variance on image stacks with distinguishable fibres or fibre-like structures.
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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.