ArticleScientific data2023
A paired dataset of T1- and T2-weighted MRI at 3 Tesla and 7 Tesla.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Clinical Research for the Use of 7 T Magnetic Resonance Imaging for Spinal Pathologies: a Scoping Review.Clinical neuroradiology · 2026Review
- CHARMS: A CNN-Transformer Hybrid with Attention Regularization for MRI Super-Resolution.Sensors (Basel, Switzerland) · 2026Article
- RAVEN: Robust, generalizable, multi-resolution structural MRI upsampling using Autoencoders.bioRxiv : the preprint server for biology · 2025Article
- Unsupervised single-image super-resolution for infant brain MRI.NeuroImage · 2025Article
- A paired CT and MRI dataset for advanced medical imaging applications.Data in brief · 2025Article
- Coil Combination Using OpTIMUS Results in Improved Signal-to-Noise Ratios of In Vivo MR Spectra Acquired at 7 T.NMR in biomedicine · 2025Article
- Advancements in the MRI technology for identification of dentomaxillofacial pathologies.European oral research · 2025Review
- A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations.Scientific data · 2025Article
- BrainAgeNeXt: Advancing brain age modeling for individuals with multiple sclerosis.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Semi-supervised synthesis of 7T MRI from 3T using 3D FR-U-Net with anatomical segmentation consistency assessment.PloS one · 2025Article
- Automated quality control of T1-weighted brain MRI scans for clinical research datasets: methods comparison and design of a quality prediction classifier.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- A paired dataset of T1- and T2-weighted MRI at 3 Tesla and 7 Tesla.Scientific data · 2023Article
- Subregional Amygdala Functional Connectivity at 3T: Comparison of High-Resolution 2D and 3D fMRI Acquisitions.Journal of neuroimaging : official journal of the American Society of NeuroimagingArticle
- RAVEN: Robust, generalizable, multi-resolution structural MRI upsampling using autoencoders.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Brain magnetic resonance imaging (MRI) provides detailed soft tissue contrasts that are critical for disease diagnosis and neuroscience research. Higher MRI resolution typically comes at the cost of signal-to-noise ratio (SNR) and tissue contrast, particularly for more common 3 Tesla (3T) MRI scanners. At ultra-high magnetic field strength, 7 Tesla (7T) MRI allows for higher resolution with greater tissue contrast and SNR. However, the prohibitively high costs of 7T MRI scanners deter their widespread adoption in clinical and research centers. To obtain higher-quality images without 7T MRI scanners, algorithms that can synthesize 7T MR images from 3T MR images are under active development. Here, we make available a dataset of paired T1-weighted and T2-weighted MR images at 3T and 7T of 10 healthy subjects to facilitate the development and evaluation of 3T-to-7T MR image synthesis models. The quality of the dataset is assessed using image quality metrics implemented in MRIQC.
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