ArticleFrontiers in artificial intelligence2022
SRflow: Deep learning based super-resolution of 4D-flow MRI data.
Article in Frontiers in artificial intelligence, 2022. 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
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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.
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.
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Who cites it
10 citing papers in PubMed.
- Jointly Learned 3D Non-Cartesian Sampling With Wave Encoding and Reconstruction for Neurovascular Phase Contrast MRI.Magnetic resonance in medicine · 2026Article
- Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.Annals of biomedical engineering · 2025Article
- Generalized Super-Resolution 4D Flow MRI - Using Ensemble Learning to Extend Across the Cardiovascular System.IEEE journal of biomedical and health informatics · 2024Article
- Unsupervised Denoising and Super-Resolution of Vascular Flow Data by Physics-Informed Machine Learning.Journal of biomechanical engineering · 2024Article
- Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities.NMR in biomedicine · 2024Review
- Super-resolution techniques for biomedical applications and challenges.Biomedical engineering letters · 2024Review
- Generalized super-resolution 4D Flow MRI-using ensemble learning to extend across the cardiovascular system.ArXiv · 2023Article
- The Potential of Deep Learning to Advance Clinical Applications of Computational Biomechanics.Bioengineering (Basel, Switzerland) · 2023Review
- Emerging Trends in Fast MRI Using Deep-Learning Reconstruction on Undersampled k-Space Data: A Systematic Review.Bioengineering (Basel, Switzerland) · 2023Review
- Advances in machine learning applications for cardiovascular 4D flow MRI.Frontiers in cardiovascular medicine · 2022Review
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
No grant is acknowledged in the PubMed record.
Abstract
Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve
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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.