Sold by: InfoBay AI Ltd.
Deployed on AWS
Sample repository from a large-scale medical imaging and radiology dataset collection containing MRI, CT, X-Ray, OPG, and Ultrasound scans with associated findings for healthcare AI, computer vision, medical imaging analysis, and clinical research.
Overview
Medical Imaging & Radiology Dataset Collection for AI Training
Overview
This dataset collection is a large-scale repository of medical imaging and radiology data designed to support healthcare AI, medical imaging analysis, computer vision, clinical research, and diagnostic intelligence applications.
The collection includes MRI, CT, X-Ray, OPG, and Ultrasound imaging datasets comprising millions of medical images and associated radiology findings. The datasets capture a diverse range of anatomical regions, imaging protocols, clinical observations, and diagnostic studies, providing comprehensive coverage for medical AI development and evaluation.
The collection combines imaging data with associated findings and clinical observations, enabling the development of AI systems capable of understanding both visual and diagnostic information within medical workflows.
Included Dataset Types
MRI Datasets
- MRI Scans without Findings
- MRI Scans with Findings
CT Datasets
- CT Scans without Findings
- CT Scans with Findings
X-Ray Datasets
- X-Ray Scans without Findings (DICOM)
- X-Ray Scans without Findings (JPEG)
- X-Ray Scans with Findings
- OPG X-Ray Scans
Ultrasound Datasets
- Ultrasound (USG) Scans with Findings
Key Features
- Large-scale medical image collection
- MRI, CT, X-Ray, OPG, and Ultrasound modalities
- DICOM and image-based datasets
- Associated radiology findings and reports
- Patient demographic metadata
- Imaging protocol information
- Anatomical and study-level metadata
- Suitable for training and evaluation workflows
Applications
This dataset collection can be used for:
- Medical Imaging AI
- Radiology AI
- Healthcare AI
- Computer Vision
- Medical Image Classification
- Disease Detection
- Diagnostic Support Systems
- Clinical Decision Support
- Medical Image Segmentation
- Image Retrieval Systems
- Multimodal Healthcare Models
- Medical Research and Analytics
Metadata Coverage
Depending on the imaging modality, metadata may include:
- Patient Age
- Patient Gender
- Study Description
- Protocol Information
- Body Part Examined
- Pixel Spacing
- Slice Thickness
- Image Orientation
- Image Position
- Hounsfield Units
- Exposure Index
- Diagnostic Findings
- Clinical Observations
Healthcare AI Development
The collection is designed to support development of next-generation healthcare AI systems capable of processing, analyzing, and interpreting medical imaging data across multiple diagnostic modalities. The diversity of imaging studies enables robust model development for clinical, research, and enterprise healthcare applications.
Licensing & Access
This listing contains sample data intended for research, evaluation, and educational purposes. Enterprise licensing and access to the complete medical imaging corpus are available upon request.
InfoBay AI
Email: datareq@infobay.ai Phone: +91 8303174762
Highlights
- Comprehensive medical imaging collection including MRI, CT, X-Ray, OPG, and Ultrasound scans with millions of associated images and radiology studies.
- Includes DICOM images, radiology findings, imaging metadata, body-part annotations, imaging protocols, and diagnostic observations across multiple modalities.
- Designed for healthcare AI, medical imaging analysis, computer vision, diagnostic support systems, radiology research, and multimodal healthcare applications.
Details
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Delivery method
Deployed on AWS
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Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
Medical Imaging & Radiology Dataset Collection for AI Training | All historical revisions | All future revisions | Not included | Not included |
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