ReviewMagma (New York, N.Y.)2025
MRI acquisition and reconstruction cookbook: recipes for reproducibility, served with real-world flavour.
Review in Magma (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- An Open-Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi-Site and Cross-Vendor Validation.Magnetic resonance in medicine · 2026Article
- MRpro: Open Framework for Model-Based, Learned, and Quantitative MR Imaging-Application to Low-Field MRI.NMR in biomedicine · 2026Article
- Article
- Disrupted drainage in the aging brain: Meningeal lymphatic decline as a convergent axis of vulnerability.Neurobiology of aging · 2026Review
- Summary from the 2025 International Society for Magnetic Resonance in Medicine workshop on body MRI: Unsolved problems and unmet needs.Magnetic resonance in medicine · 2026Review
- A vendor-neutral functional MRI acquisition protocol for multi-site studies.Aperture neuro · 2026Article
- Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI.Physics in medicine and biology · 2025Article
- Res-MoCoDiff: Residual-guided diffusion models for motion artifact correction in brain MRI.ArXiv · 2025Article
- Reproducibility and quality assurance in MRI.Magma (New York, N.Y.) · 2025Article
- Rethinking MRI as a measurement device through modular and portable pipelines.Magma (New York, N.Y.) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
MRI acquisition and reconstruction research has transformed into a computation-driven field. As methods become more sophisticated, compute-heavy, and data-hungry, efforts to reproduce them become more difficult. While the computational MRI research community has made great leaps toward reproducible computational science, there are few tailored guidelines or standards for users to follow. In this review article, we develop a cookbook to facilitate reproducible research for MRI acquisition and reconstruction. Like any good cookbook, we list several recipes, each providing a basic standard on how to make computational MRI research reproducible. And like cooking, we show example flavours where reproducibility may fail due to under-specification. We structure the article, so that the cookbook itself serves as an example of reproducible research by providing sequence and reconstruction definitions as well as data to reproduce the experimental results in the figures. We also propose a community-driven effort to compile an evolving list of best practices for making computational MRI research reproducible.
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.