datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multimodal-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.mirabest-radio-astronomy-unofficial
MiraBest Radio Astronomy Dataset (Unofficial)
⚠️ IMPORTANT: This is an unofficial repository containing a processed version of the MiraBest dataset formatted for stable diffusion fine-tuning. This repository is not affiliated with the original authors.
Unofficial processing of the MiraBest radio astronomy dataset with original classification labels and natural language captions for diffusion fine-tuning. Original dataset by Porter & Scaife (2023).
Original Dataset
The… See the full description on the dataset page: https://huggingface.co/datasets/kwazzi-jack/mirabest-radio-astronomy-unofficial.MRI-Radiology-Reports-Without-Findings-Dataset
InfoBay.AI Healthcare Imaging Dataset Catalogue
Overview
The InfoBay.AI Healthcare Imaging Dataset Catalogue is one of the largest enterprise-scale collections of medical imaging and clinical healthcare records curated for Artificial Intelligence, Computer Vision, Medical Imaging Research, Large Multimodal Models (LMMs), Vision Language Models (VLMs), Diagnostic AI, and Healthcare Analytics.
The catalogue contains 112 Million+ medical files and images collected… See the full description on the dataset page: https://huggingface.co/datasets/InfoBayAI/MRI-Radiology-Reports-Without-Findings-Dataset.radiology-ready-v2
Radiology Ready v2
Training-ready dataset for fine-tuning the Radiology agent of an AI Medical Department,
built on MedGemma 1.5-4B-IT.
Each row is a (prompt, response) pair ready for SFT. CT scan images are not stored here —
they live in UngLong/openm3chest-npy-v2
and are fetched at training time via {pids}/{keys}.npy.
Dataset Summary
Rows
500
Screening rows
302 (Pool A + Pool B)
Detail rows
198 (Pool A — nodule present)
Unique CT volumes
477… See the full description on the dataset page: https://huggingface.co/datasets/UngLong/radiology-ready-v2.radiology-test-v2
Radiology Test v2
Evaluation dataset for the Radiology agent of an AI Medical Department,
paired with UngLong/radiology-ready-v2
(training set). CT images are in UngLong/openm3chest-npy-v2.
⚠️ Before using: CT scans for this test set must be uploaded to openm3chest-npy-v2 first.
See scripts/test_npy_needed.txt (154 scan keys) for the list to upload via build_npy_hub.py.
Dataset Summary
Total rows
154
Screening rows
74 (all 8 screening tasks)… See the full description on the dataset page: https://huggingface.co/datasets/UngLong/radiology-test-v2.Radio_lentille
Terres Inovia - Dataset d'Essais radio lentille bruchée
Description du Dataset
Ce dataset est fourni par Terres Inovia, l’institut technique de la filière des huiles et protéines végétales et de la filière chanvre. Le jeu de données contient 807 images au format JPG, collectées lors d’essais agronomiques avec un accent particulier sur l'analyse de la qualité des graines de lentilles. Le caractère observé est la quantité de graines atteintes par la bruche de la lentille.… See the full description on the dataset page: https://huggingface.co/datasets/JeanEudesH/Radio_lentille.