UltraCortex: Submillimeter Ultra-High Field 9.4 T Brain MR Image Collection and Manual Cortical Segmentations
Not on the map. Why?
Abstract (arXiv)
The UltraCortex repository (https://www.ultracortex.org) houses magnetic resonance imaging data of the human brain obtained at an ultra-high field strength of 9.4 T. It contains 86 structural MR images with spatial resolutions ranging from 0.6 to 0.8 mm. Additionally, the repository includes segmentations of 12 brains into gray and white matter compartments. These segmentations have been independently validated by two expert neuroradiologists, thus establishing them as a reliable gold standard. This resource provides researchers with access to high-quality brain imaging data and validated segmentations, facilitating neuroimaging studies and advancing our understanding of brain structure and function. Existing repositories do not accommodate field strengths beyond 7 T, nor do they offer validated segmentations, underscoring the significance of this new resource.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 1 of its 25 references that are in the map. First posted on arXiv 3 Jun 2024.
Builds on
1 of 25 references.
References · 1
- 2022SynthStrip: Skull-Stripping for Any Brain Imagecited by 126
Built on by
Citing papers per year: 2024: 1; 2025: 4; 2026: 1.
6 papers.
- 2024An OpenMind for 3D medical vision self-supervised learningcited by 23
- 2025Beyond the LUMIR challenge: The pathway to foundational registration modelscited by 12
- 2025A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learningcited by 7
- 2025Encoder-Only Image Registrationcited by 3
- 2025The LUMirage: An independent evaluation of zero-shot performance in the LUMIR challengecited by 2
- 2026SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Trainingcited by 2
- 2026SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Training4 May 2026
- 2025The LUMirage: An independent evaluation of zero-shot performance in the LUMIR challenge17 Dec 2025
- 2025Encoder-Only Image Registration30 Aug 2025
- 2025A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning17 Jun 2025
- 2025Beyond the LUMIR challenge: The pathway to foundational registration models30 May 2025
- 2024An OpenMind for 3D medical vision self-supervised learning22 Dec 2024