datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NIH-Chest-X-ray-datasetThe NIH Chest X-ray dataset consists of 100,000 de-identified images of chest x-rays. The images are in PNG format.
The data is provided by the NIH Clinical Center and is available through the NIH download site: https://nihcc.app.box.com/v/ChestXray-NIHCCnih-chest-xray
NIH ChestX-ray14 — WebDataset
Dataset original: nih-chest-xrays/data
Imágenes: 112,120 PNGs en escala de grises (1024×1024)
Formato: WebDataset (TAR archives, ~1000 imágenes por TAR)
Split: train
Cómo cargar
from datasets import load_dataset
ds = load_dataset("webdataset", data_dir="yeigen/nih-chest-xray", split="train", streaming=True)
for sample in ds:
img = sample["png"] # PIL Image
print(img.size)
break
vinbigdata-chest-xray-abnormalities-png
VinBigData Chest X-ray Abnormalities (Private Processed Mirror)
Private repository for personal transfer / research use only. Do not redistribute.
Derived from the VinBigData Chest X-ray Abnormalities Detection / VinDr-CXR dataset. Original data is subject to the VinBigdata / PhysioNet data use agreement; keep this repo private and do not share access with third parties.
Contents
Path
Description
image/train/*.png
4394 train images with abnormalities… See the full description on the dataset page: https://huggingface.co/datasets/ASD9987/vinbigdata-chest-xray-abnormalities-png.chest-xray-classification
Dataset Labels
['NORMAL', 'PNEUMONIA']
Number of Images
{'train': 4077, 'test': 582, 'valid': 1165}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/chest-xray-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/2
Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/chest-xray-classification.Multimodal-Chest-X-ray-dataset-for-Normal-and-Bacterial-Pneumonia-in-Africans
Multimodal Chest X ray dataset for Normal and Bacterial Pneumonia in Africans | Africa (Electric Sheep Africa metadata inventory)
Size category: 1K<n<10K - Formats: imagefolder - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/Multimodal-Chest-X-ray-dataset-for-Normal-and-Bacterial-Pneumonia-in-Africans.NIH-Chest-XRay-Federated
NIH Chest X-ray Federated Learning Dataset
Federated learning splits designed for the [Cold Start:] Distributed AI Hack Berlin 2025.
The dataset is based on the NIH Chest X-ray14 dataset, which contains ~112,000 X-ray images from 30,805 unique patients, and models a federated learning scenario with non-IID characteristics across three hospitals, plus an out-of-distribution test set.
Dataset Description
The data was partitioned using a scoring algorithm that creates… See the full description on the dataset page: https://huggingface.co/datasets/exalsius/NIH-Chest-XRay-Federated.chest-xray-14-320
NIH Chest X-ray14 - 320x320 Processed for CheXVision
Project Resources
GitHub repository
Presentation deck
Live demo
Scratch model
DenseNet model
This dataset repackages the raw NIH Chest X-ray14 source dataset from
alkzar90/NIH-Chest-X-ray-dataset
into a data-only Parquet dataset for the CheXVision project.
Dataset Summary
Source format: 12 ZIP archives of original chest X-ray images plus CSV manifests
Output format: data-only Parquet shards under data/… See the full description on the dataset page: https://huggingface.co/datasets/arudaev/chest-xray-14-320.chestx
Dataset Structure
This dataset contains vision data for chest X-ray pathology identification.
Data Fields
image: The PIL image of the chest X-ray. These images are size (224,224) by default.
pathols: A binary-valued (14)-shaped array that indicates whether each of the 14 pathologies is present.
structs: A binary-valued array of shapes (14,224,224) that gives the segmentation for each of the 14 anatomical structures.
The 14 pathologies are:
Atelectasis
Cardiomegaly… See the full description on the dataset page: https://huggingface.co/datasets/BrachioLab/chestx.chest-xray-tb-pneumonia
Chest X-Ray: Tuberculosis, Pneumonia & Normal
A curated chest X-ray image dataset for three-class classification: NORMAL, PNEUMONIA, and TUBERCULOSIS.
Derived from public sources (NIH Chest X-ray Dataset, RSNA Pneumonia Detection Challenge, Kaggle TB datasets) and split into train/validation/test sets.
Dataset Structure
final_dataset/
├── train/ # 9,097 images (NORMAL=3,911 | PNEUMONIA=2,971 | TUBERCULOSIS=2,215)
├── val/ # 1,950 images… See the full description on the dataset page: https://huggingface.co/datasets/realsudarshan/chest-xray-tb-pneumonia.conflux-chest-ct
CONFLUX Chest-CT
200,000 synthetic 3D chest CT volumes with structured abnormality and demographic labels, generated by CONFLUX.
Released with the paper CONFLUX: A Latent Diffusion Model for 3D Chest-CT Synthesis with RL Post-Training.
Paper (arXiv) •
Model •
Code — coming soon
About
CONFLUX is a conditional 3D latent generative model for chest CT: a VAE tokenizer
compresses each volume into a compact 16-channel latent, a… See the full description on the dataset page: https://huggingface.co/datasets/gevaertlab/conflux-chest-ct.chest-xray-14
NIH Chest X-ray14 — Processed for CheXVision
This dataset wraps the NIH Chest X-ray14 dataset, preprocessed for the CheXVision project.
Labels
Label
Count
Prevalence
Infiltration
19,894
17.7%
Effusion
13,317
11.9%
Atelectasis
11,559
10.3%
Nodule
6,331
5.6%
Mass
5,782
5.2%
Pneumothorax
5,302
4.7%
Consolidation
4,667
4.2%
Pleural_Thickening
3,385
3.0%
Cardiomegaly
2,776
2.5%
Emphysema
2,516
2.2%
Edema
2,303
2.1%
Fibrosis
1,686
1.5%… See the full description on the dataset page: https://huggingface.co/datasets/arudaev/chest-xray-14.africa-synth-tuberculosis-chest-ctscan-african-ehr-all
Chest CT Scans + Synthetic African EHR (Lung Cancer) | Africa (Electric Sheep Africa metadata inventory)
Size category: 1K<n<10K - Formats: imagefolder - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-tuberculosis-chest-ctscan-african-ehr-all.chest-xray-14
NIH Chest X-ray14 — Processed for CheXVision
This dataset wraps the NIH Chest X-ray14 dataset, preprocessed for the CheXVision project.
Labels
Label
Count
Prevalence
Infiltration
19,894
17.7%
Effusion
13,317
11.9%
Atelectasis
11,559
10.3%
Nodule
6,331
5.6%
Mass
5,782
5.2%
Pneumothorax
5,302
4.7%
Consolidation
4,667
4.2%
Pleural_Thickening
3,385
3.0%
Cardiomegaly
2,776
2.5%
Emphysema
2,516
2.2%
Edema
2,303
2.1%
Fibrosis
1,686
1.5%… See the full description on the dataset page: https://huggingface.co/datasets/Sharon2105/chest-xray-14.chest-xray-classification
Dataset Labels
['PNEUMONIA', 'NORMAL']
Number of Images
{'test': 582, 'valid': 1165, 'train': 12230}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("trpakov/chest-xray-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/3
Citation
License… See the full description on the dataset page: https://huggingface.co/datasets/trpakov/chest-xray-classification.chest_xray
Zoidberg2.0
The data has been taken from kaggle
Usage
Install Hugging Face's datasets library
pip install datasets
Load the dataset with the following lines
from datasets import load_dataset
dataset = load_dataset("Az-r-ow/chest_xray")
For more information on how to manipulate the data checkout the docs
synthetic-chest-xray-pneumonia
Synthetic Chest X-Ray Pneumonia Dataset
Dataset Description
This dataset contains synthetic chest X-ray images generated using Stable Diffusion 2.1
fine-tuned with DreamBooth on the hf-vision/chest-xray-pneumonia dataset.
Purpose
Created for a science fair project investigating whether synthetic medical images generated
by diffusion models can improve pneumonia classifier accuracy.
Research Question
Can synthetic chest X-ray images generated by a… See the full description on the dataset page: https://huggingface.co/datasets/chimbiwide/synthetic-chest-xray-pneumonia.chest-bench-example
ChestBench Example
DICOM-VLM Framework Reference Package v0.2.0
ChestBench Example is a four-case, DICOM-native reference package for developing and validating the data architecture of a medical vision-language model (VLM) pipeline.
It is intentionally small. Its purpose is to demonstrate how medical imaging data, annotations, text, knowledge, retrieval targets, QA, evidence requirements, perturbations, and audit metadata can be represented without confusing… See the full description on the dataset page: https://huggingface.co/datasets/NeeyuHuynh/chest-bench-example.chest-xray-14
NIH Chest X-ray14 Dataset
Dataset Description
This dataset contains 112120 chest X-ray images with multiple disease labels per image.
Labels
Atelectasis, Cardiomegaly, Consolidation, Edema, Effusion, Emphysema, Fibrosis, Hernia, Infiltration, Mass, No Finding, Nodule, Pleural_Thickening, Pneumonia, Pneumothorax
Dataset Structure
Train split: 78484 images
Validation split: 16818 images
Test split: 16818 images
Data Format
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Manas2703/chest-xray-14.NIH-Chest-X-ray-datasetThe NIH Chest X-ray dataset consists of 100,000 de-identified images of chest x-rays. The images are in PNG format.
The data is provided by the NIH Clinical Center and is available through the NIH download site: https://nihcc.app.box.com/v/ChestXray-NIHCCchest-xray
Chest-Xray (Teeny-Tiny Castle)
This dataset is part of a tutorial tied to the Teeny-Tiny Castle, an open-source repository containing educational tools for AI Ethics and Safety research.
How to Use
from datasets import load_dataset
dataset = load_dataset("AiresPucrs/chest-xray", split = 'train')
chest-xray-pneumonia-3class-balanced
Chest X-Ray (Pneumonia) — 3-class balanced (opencampus Week 6)
Prepared dataset for the opencampus applied ML Week 6 assignment.
Classes
NORMAL
BACTERIAL_PNEUMONIA
VIRAL_PNEUMONIA
Layout
chest_xray/
├── train/
└── val/
unseen/
Colab / notebook download
For Google Colab, download the prepared archive (~1 GB) and pretrained weights from this repo:
chest_xray_prepared.zip — contains chest_xray/ and unseen/
resnet18_chest_xray_classifier_weights.pth… See the full description on the dataset page: https://huggingface.co/datasets/opencampus/chest-xray-pneumonia-3class-balanced.chest-xray-images
Please read this paper about evaluation issues: https://arxiv.org/abs/2004.12823 and https://arxiv.org/abs/2004.05405
COVID-19 image data collection (🎬 video about the project)
Project Summary: To build a public open dataset of chest X-ray and CT images of patients which are positive or suspected of COVID-19 or other viral and bacterial pneumonias (MERS, SARS, and ARDS.). Data will be collected from public sources as well as through indirect collection from hospitals and… See the full description on the dataset page: https://huggingface.co/datasets/pulmo/chest-xray-images.CHEST-XRAY-CPE-OPH2025
CHEST-XRAY-CPE-OPH2025
Description
This dataset is a curated subset of Chest X-Ray Images (Pneumonia) from kaggle.It was specifically prepared for educational purposes in the KMUTT CPE OpenHouse 2025 workshop.
Only selected classes of Thai food are included, and corrupted images were removed to ensure smooth training and evaluation. The dataset provides labeled images of Chest X-Ray, useful for practicing deep learning workflows such as preprocessing, training, and… See the full description on the dataset page: https://huggingface.co/datasets/Thinnaphat/CHEST-XRAY-CPE-OPH2025.chest-xrays-evaluation_cnn-cls
🩻 Chest X-Ray: Detección de Anomalías
Dataset de imágenes de radiografías de tórax procesadas para tareas de clasificación binaria (Normal vs Anomalía). Este dataset forma parte del curso de Deep Learning de inGeniia, utilizado para enseñar Redes Convolucionales (CNN) y Transfer Learning con modelos como YOLO11 (modo clasificación).
🖼️ Descripción del Dataset
Las imágenes han sido extraídas originalmente de Kaggle y procesadas con técnicas de Data Augmentation para… See the full description on the dataset page: https://huggingface.co/datasets/inGeniia/chest-xrays-evaluation_cnn-cls.synthetic_chest_xrayChest XRay dataset with chexpert labels.chest-xrays-evaluation_cnn-cls
🩻 Chest X-Ray: Detección de Anomalías
Dataset de imágenes de radiografías de tórax procesadas para tareas de clasificación binaria (Normal vs Anomalía). Este dataset forma parte del curso de Deep Learning de inGeniia, utilizado para enseñar Redes Convolucionales (CNN) y Transfer Learning con modelos como YOLO11 (modo clasificación).
🖼️ Descripción del Dataset
Las imágenes han sido extraídas originalmente de Kaggle y procesadas con técnicas de Data Augmentation para… See the full description on the dataset page: https://huggingface.co/datasets/edgardoporto/chest-xrays-evaluation_cnn-cls.autotrain-data-big-data-chest
AutoTrain Dataset for project: big-data-chest
Dataset Description
This dataset has been automatically processed by AutoTrain for project big-data-chest.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<2090x1858 L PIL image>",
"target": 0
},
{
"image": "<1422x1152 L PIL image>",
"target": 0
}]
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/MartinLubenov/autotrain-data-big-data-chest.chest_x_ray
Dataset Card for NIH Chest X-ray dataset
Dataset Summary
ChestX-ray dataset comprises 112,120 frontal-view X-ray images of 30,805 unique patients with the text-mined fourteen disease image labels (where each image can have multi-labels), mined from the associated radiological reports using natural language processing. Fourteen common thoracic pathologies include Atelectasis, Consolidation, Infiltration, Pneumothorax, Edema, Emphysema, Fibrosis, Effusion, Pneumonia… See the full description on the dataset page: https://huggingface.co/datasets/Shee2001/chest_x_ray.