ArticleNeuroImage2019
Joint modelling of diffusion MRI and microscopy.
Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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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.
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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.
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Who cites it
22 citing papers in PubMed, 32 citations in OpenAlex.
- Microscopy-informed structural connectivity mapping in the in vivo human brain via domain adaptation.bioRxiv : the preprint server for biology · 2026Article
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Sampling of non-Gaussian Ensemble Average Propagators for the simulation of diffusion magnetic resonance images.Magnetic resonance in medicine · 2026Article
- Diffusion-weighted steady-state free precession imaging in the ex vivo macaque brain on a 10.5T human MRI scanner.bioRxiv : the preprint server for biology · 2025Article
- Clinically feasible liver tumour cell size measurement through histology-informed in vivo diffusion MRI.Communications medicine · 2025Article
- Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3-Ex vivo imaging: Data processing, comparisons with microscopy, and tractography.Magnetic resonance in medicine · 2025Review
- Imaging the structural connectome with hybrid MRI-microscopy tractography.Medical image analysis · 2025Article
- The scientific value of tractography: accuracy vs usefulness.Brain structure & function · 2025Article
- An open resource combining multi-contrast MRI and microscopy in the macaque brain.Nature communications · 2023Article
- Gradients of neurotransmitter receptor expression in the macaque cortex.Nature neuroscience · 2023Article
- Using mesoscopic tract-tracing data to guide the estimation of fiber orientation distributions in the mouse brain from diffusion MRI.NeuroImage · 2023Article
- versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database.Frontiers in neuroinformatics · 2023Article
- Review
- What's new and what's next in diffusion MRI preprocessing.NeuroImage · 2022Review
- Article
- Prevalence of white matter pathways coming into a single white matter voxel orientation: The bottleneck issue in tractography.Human brain mapping · 2022Article
- Histopathological modeling of status epilepticus-induced brain damage based onFrontiers in neuroscience · 2022Article
- Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain.Human brain mapping · 2021Article
- The sensitivity of diffusion MRI to microstructural properties and experimental factors.Journal of neuroscience methods · 2021Review
- Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging.IEEE transactions on medical imaging · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
The combination of diffusion MRI (dMRI) with microscopy provides unique opportunities to study microstructural features of tissue, particularly when acquired in the same sample. Microscopy is frequently used to validate dMRI microstructure models, addressing the indirect nature of dMRI signals. Typically, these modalities are analysed separately, and microscopy is taken as a gold standard against which dMRI-derived parameters are validated. Here we propose an alternative approach in which we combine dMRI and microscopy data obtained from the same tissue sample to drive a single, joint model. This simultaneous analysis allows us to take advantage of the breadth of information provided by complementary data acquired from different modalities. By applying this framework to a spherical-deconvolution analysis, we are able to overcome a known degeneracy between fibre dispersion and radial diffusion. Spherical-deconvolution based approaches typically estimate a global fibre response function to determine the fibre orientation distribution in each voxel. However, the assumption of a 'brain-wide' fibre response function may be challenged if the diffusion characteristics of white matter vary across the brain. Using a generative joint dMRI-histology model, we demonstrate that the fibre response function is dependent on local anatomy, and that current spherical-deconvolution based models may be overestimating dispersion and underestimating the number of distinct fibre populations per voxel.
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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.