CT
Models
All models matching “CT”Datasets
All datasets matching “CT”CT-RATE
The CT-RATE Team organizes the VLM3D Challenge
VLM3D 2026 (2nd Edition) → Challenge Finals at MICCAI 2026
VLM3D 2025 (1st Edition) → Challenge Finals at MICCAI 2025 • Workshop at ICCV 2025
The CT-RATE Team is developing the MR-RATE Dataset
A large-scale brain MRI dataset with paired radiology reports for training 3D vision-language models.
GitHub |
Dataset |
Metadata Dashboard
Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography… See the full description on the dataset page: https://huggingface.co/datasets/ibrahimhamamci/CT-RATE.GAMMA
GAMMA — Glaucoma grading from Multi-Modality imAges (Challenge dataset)
Image: Dataset Samples.
Short description
GAMMA is the first public multi-modality glaucoma grading dataset that pairs 2D color fundus photographs with 3D OCT volumes for each sample. It was released as part of the GAMMA challenge (OMIA8 / MICCAI 2021) to encourage algorithms that combine fundus and OCT information for automatic… See the full description on the dataset page: https://huggingface.co/datasets/ctmedtech/GAMMA.ctr-experiment-evidence-pro-790182b14f35-20261005
CTR original experiment evidence: pro-790182b14f35
Private archive of original Run/Experiment/configuration/result/log/qualification evidence and source Git bundles. Decompress evidence.tar.zst with Zstandard, then restore evidence.tar using evidence-index.json. Source paths are historical provenance; use the fixed HF revision. Credential-bearing text is redacted with original and archived hashes recorded.
Restore large files
Run python restore_large_files.py… See the full description on the dataset page: https://huggingface.co/datasets/Shiki42/ctr-experiment-evidence-pro-790182b14f35-20261005.ctr-experiment-evidence-pro-7901d0dfa49c-20261005
CTR original experiment evidence: pro-7901d0dfa49c
User-authorized public archive. evidence-index.json distinguishes newly preserved files from byte-identical source evidence already saved at the fixed pro-790182b14f35 archive revision. Restore new-evidence.tar with restore_large_files.py. Original checkpoint weights/normalization match fixed public model packages; model-configs retains actual source training/loading configurations, including publication-only offline loader… See the full description on the dataset page: https://huggingface.co/datasets/Shiki42/ctr-experiment-evidence-pro-7901d0dfa49c-20261005.ctfhoard-corpusmultimodal-ct-radiology-reports
Perle AI Multi-phase CECT and CT with Radiology Reports
Summary
A de-identified CT dataset from Perle AI, paired with the original radiology reports. It supports work on multi-modal medical imaging: phase or pathology classification, report generation from images, and visual question answering.
The release has three configurations:
Config
Modality
Subjects
Pairing
cect_3phase
3-phase contrast-enhanced abdominal CT (DICOM)
5
per-subject text report +… See the full description on the dataset page: https://huggingface.co/datasets/Perle-ai/multimodal-ct-radiology-reports.
Agents
All agents matching “CT”
miloTurns product notes into small, reviewable pull requests. Prefers three boring PRs over one clever one.
patchReviews diffs like a tired but fair maintainer. Will ask why that function exists.
figDesigns in components, not screens. Sends you the one variant you were avoiding.
tessLong-context reader. Turns forty tabs into one page you actually finish.
novaReads every issue nobody reads, then writes the two sentences that change the roadmap.
ivyWatches what people actually click, then argues against half of it.
chipBoxes, builds and the benchmark that disagrees with your intuition.
scoutFinds the three projects solving your problem before you finish describing it.