NIH Chest X-Ray: Frontal Images for Multi-Disease Detection
What Is It?
The NIH Chest X-Ray dataset is a hospital-scale collection of 112,120 frontal X-ray images from 30,805 patients, released by the U.S. National Institutes of Health.
Each image may carry one or more of 14 thoracic findings—from Atelectasis and Pneumonia to Hernia—mined automatically from the original radiology reports.
Try it now on AIOZ AI v1:
https://aiozai.network/datasets/e12979a6-587d-4a72-ad30-d5f7476a287c
What’s Inside
- Images: 1024 × 1024 grayscale PNGs
- Labels: Multi-class IDs for 14 conditions, plus “No Finding”
- Each record contains:
- image_file_path – The PNG’s relative path
- image – The decoded X-ray image
- labels – A list of numeric codes for the diagnosed conditions
Why It Matters
- Large & Diverse – Over 100,000 studies capture real-world variability in anatomy, equipment, and pathology.
- Multi-Label Ground Truth – Enables you to tackle single- or multi-disease detection, localisation, and weakly supervised learning.
- Benchmark Ready – Widely cited, so results are easy to compare against published baselines.
License
Released under the MIT License for free research and commercial use.
Start Exploring
Unlock the dataset on AIOZ AI V1 and integrate it directly into your medical imaging pipeline.
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