|
1 | | -WIP |
| 1 | +## Suggested public datasets |
| 2 | + |
| 3 | + |
| 4 | +### PET/CT |
| 5 | +> Note that all PET images in the following datasets are attenuation corrected (usually by the accompanying CT), which means that the PET may encode some of the CT information. |
| 6 | +- [Vienna QUADRA_HC](https://zenodo.org/records/16588733) 100 whole-body 18F-FDG PET/CT studies from 50 participants. Like BIC-MAC, the PET/CT is acquired on a Siemens Biograph Vision Quadra and the participants are healthy controls. [citation](https://www.nature.com/articles/s41597-025-05997-4) |
| 7 | + |
| 8 | +- [AutoPET V](https://fdat.uni-tuebingen.de/records/0zs4c-89f12) 1014 whole-body 18F-FDG PET/CT studies, 597 PSMA PET/CT studies [citation](https://www.nature.com/articles/s41597-022-01718-3) |
| 9 | + |
| 10 | +- [PETWB-REP](https://zenodo.org/records/18670487) 565 whole-body 18F-FDG PET/CT studies [citation](https://arxiv.org/pdf/2508.04062) |
| 11 | + |
| 12 | +- [ENHANCE.PET](https://pubmed.ncbi.nlm.nih.gov/40799763/) 1,597 whole-body 18F-FDG PET/CT studies. Downloaded by running `moosez -dtd -dd path/to/download/` (install [moosez](https://github.com/ENHANCE-PET/MOOSE)) [citation](https://pmc.ncbi.nlm.nih.gov/articles/PMC12340901/#S1). |
| 13 | + |
| 14 | +- [ViMED-PET](https://huggingface.co/datasets/dacthai2807/ViMed-PET) 2,757 whole-body 18F-FDG PET/CT studies. [citation](https://arxiv.org/abs/2509.24739v1) |
| 15 | + |
| 16 | +- [Lung-PET-CT-Dx](https://www.cancerimagingarchive.net/collection/lung-pet-ct-dx/) 436 whole-body (no head) 18F-FDG PET/CT studies [citation](https://doi.org/10.7937/TCIA.2020.NNC2-0461) |
| 17 | + |
| 18 | +### MRI/CT |
| 19 | + |
| 20 | +- [SynthRAD2025](https://zenodo.org/records/14918089) 890 paired MRI–CT and 1,472 CBCT–CT sets covering head-and-neck, thorax, and abdomen from 5 European university medical centers. [citation](https://arxiv.org/abs/2502.17609) |
| 21 | + |
| 22 | +- [CHAOS](https://zenodo.org/records/3431873) 40 abdominal CT and 40 abdominal MRI studies (T1-DUAL, T2-SPIR) from healthy subjects. CT and MRI are from **different** patients (unpaired). [citation](https://doi.org/10.1016/j.media.2020.101950) |
| 23 | + |
| 24 | +- [Paired CT–MRI (T1+T2)](https://doi.org/10.1016/j.dib.2025.111768) Small co-registered CT and MRI (T1- and T2-weighted) dataset from the same patients. [citation](https://doi.org/10.1016/j.dib.2025.111768) |
| 25 | + |
| 26 | +- [Learn2Reg Abdomen MR-CT](https://learn2reg.grand-challenge.org/Datasets/) 16 paired and 90 unpaired abdominal CT and MRI scans [citation](https://doi.org/10.1109/TMI.2022.3213983) |
| 27 | + |
| 28 | +- [RIRE](https://rire.insight-journal.org/) ~20 brain patients with paired CT, T1, T2, and PD MRI with gold-standard marker-based registration transforms. [citation](https://rire.insight-journal.org/) |
| 29 | + |
| 30 | + |
| 31 | +### CT |
| 32 | + |
| 33 | +- [NLST](https://www.cancerimagingarchive.net/collection/nlst/) ~26,000 low-dose chest CT studies. [citation](https://doi.org/10.7937/TCIA.HMQ8-J677) |
| 34 | + |
| 35 | +- [CT-RATE](https://huggingface.co/datasets/ibrahimhamamci/CT-RATE) 47,149 chest CT volumes with paired radiology reports. [citation](https://huggingface.co/datasets/ibrahimhamamci/CT-RATE) |
| 36 | + |
| 37 | +- [TotalSegmentator CT](https://zenodo.org/records/10047292) 1,228 whole-body CT studies with segmentations of 117 anatomical structures. [citation](https://doi.org/10.1148/ryai.230024) |
| 38 | + |
| 39 | +- [AbdomenAtlas 1.0 Mini](https://huggingface.co/datasets/AbdomenAtlas/AbdomenAtlas1.0Mini) 5,195 abdominal CT studies with 9-organ segmentations. [citation](https://arxiv.org/abs/2305.09666) |
| 40 | + |
| 41 | +### MRI |
| 42 | +- [TotalSegmentator MRI](https://zenodo.org/records/14710732) 616 whole-body MRI studies. [citation](https://doi.org/10.1148/ryai.230024) |
| 43 | + |
| 44 | +- [FOMO-300K](https://huggingface.co/datasets/FOMO-MRI/FOMO300K) 81,282 brain MRI studies with a total of 306,303 scans. [citation](https://arxiv.org/abs/2506.14432) |
| 45 | + |
| 46 | +### Chest X-ray (Topogram-like) |
| 47 | +- [CheXpert](https://stanfordmlgroup.github.io/competitions/chexpert/) 224,316 chest radiographs of 65,240 patients with 14 pathology labels. [citation](https://arxiv.org/abs/1901.07031) |
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