ArticleImaging neuroscience (Cambridge, Mass.)2024
Internally consistent and fully unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM.
Article in Imaging neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Evaluating the quality of brainstem ROI registration using structural and diffusion MRI.Frontiers in neuroscience · 2026Article
- Construction of a Structurally Unbiased Brain Template with High Image Quality from MRI Scans of Saudi Adult Females.Bioengineering (Basel, Switzerland) · 2025Article
- MRI-scale histology validates spatial sensitivity of in-vivo MRI-based axon radius estimation.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- MMORF-FSL's MultiMOdal Registration Framework.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Internally consistent and fully unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM.Imaging neuroscience (Cambridge, Mass.) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Anatomical magnetic resonance imaging (MRI) templates of the brain are essentialto group-level analyses and image processing pipelines, as they provide areference space for spatial normalisation. While it has become common forstudies to acquire multimodal MRI data, many templates are still limited to onetype of modality, usually either scalar or tensor based. Aligning each modalityin isolation does not take full advantage of the available complementaryinformation, such as strong contrast between tissue types in structural images,or axonal organisation in the white matter in diffusion tensor images. Mostexisting strategies for multimodal template construction either do not use allmodalities of interest to inform the template construction process, or do notuse them in a unified framework. Here, we present multimodal, cross-sectionaltemplates constructed from UK Biobank data: the Oxford-MultiModal-1 (OMM-1)template and age-dependent templates for each year of life between 45 and 81years. All templates are fully unbiased to represent the average shape of thepopulations they were constructed from, and internally consistent throughjointly informing the template construction process with T1-weighted (T1),T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and diffusion tensorimaging (DTI) data. The OMM-1 template was constructed with a multiresolution,iterative approach using 240 individuals in the 50-55-year age range. Theage-dependent templates were estimated using a Gaussian process, which describesthe change in average brain shape with age in 37,330 individuals. All templatesshow excellent contrast and alignment within and between modalities. The globalbrain shape and size are not preconditioned on existing templates, althoughmaximal possible compatibility with MNI-152 space was maintained through rigidalignment. We showed benefits in registration accuracy across two datasets (UKBiobank and HCP), when using the OMM-1 as the template compared withFSL's MNI-152 template, and found that the use of age-dependent templatesfurther improved accuracy to a small but detectable extent. All templates arepublicly available and can be used as a new reference space for uni- ormultimodal spatial alignment.
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.