52M+ CT Scan Images with Radiology Findings Dataset
Medical Imaging Data
Tags and Keywords
£75,000
About
52M+ CT Scan Images with Radiology Findings Dataset
Description
The 52M+ CT Scan Images with Radiology Findings Dataset is a large-scale medical imaging dataset developed for artificial intelligence, computer vision, radiology research, and healthcare analytics. The dataset contains over 52M+ Computed Tomography (CT) scan images collected from 185K+ anonymized patients in DICOM format, paired with corresponding radiology findings in PDF reports. It is designed to support the development of AI-powered diagnostic systems, medical image analysis models, disease detection algorithms, multimodal learning, and clinical decision support applications. Covering diverse anatomical regions and radiological observations, this dataset provides high-quality medical imaging data for research, model training, validation, and commercial AI development.
Note: The listed price applies to the specified initial batch of 10,000 image-report pairs. Pricing for larger batches or the complete dataset library varies based on the number of image-report pairs, image quality and resolution, metadata availability, annotation requirements, imaging modality, file formats, licensing terms, and customization needs. Final pricing will be determined based on the specific dataset requirements.
Data Product Features
| Feature | Description |
|---|---|
| CT Scan Image | Computed Tomography (CT) image stored in DICOM format. |
| Radiology Findings | Radiologist interpretation associated with the CT examination. |
| Modality | Imaging modality (CT). |
| Body Region | Anatomical region scanned (Brain, Chest, Abdomen, Pelvis, Spine, etc.). |
| Findings Summary | Summary of radiological observations. |
| Report File | Corresponding radiology report in PDF format. |
| Image Dimensions | Resolution and image size information. |
Distribution
- Dataset Format: DICOM (.dcm), PDF (.pdf)
Data Volume
- 52M+ CT Scan Images
- 185K+ anonymized patients
- Multiple CT studies across various anatomical regions
- High-resolution DICOM medical imaging files
- Dataset Size: The dataset size may vary depending on image resolution, image dimensions, compression quality, metadata availability, diagnostic findings, annotations, and dataset version.
Usage
This dataset is ideal for a variety of healthcare AI and medical imaging applications:
- Medical Image Classification: Train AI models to classify CT scan images.
- Disease Detection: Develop algorithms for detecting tumors, fractures, hemorrhage, infections, lung diseases, and other abnormalities.
- Medical Image Segmentation: Build models for organ, tissue, and lesion segmentation.
- Radiology AI: Develop automated radiology interpretation and reporting systems.
- Computer Vision: Train deep learning models for medical image understanding.
- Clinical Decision Support: Build AI systems to assist clinicians in diagnostic workflows.
- Vision-Language Models: Train multimodal AI models using CT images and radiology findings.
- Medical Report Analysis: Extract structured clinical information from radiology reports.
- Academic Research: Support research in radiology, healthcare AI, and medical image analysis.
Coverage
- Geographic Coverage: Global
License
CC BY 4.0 (Creative Commons Attribution 4.0 International)
AI Training Rights
InfoBay.AI ensures that all datasets are sourced, curated, and managed with proper ownership verification, licensing documentation, and data provenance records. We hold the necessary rights to license and sublicense the datasets we provide through formal agreements with our data vendors, which grant us the required permissions for commercial licensing and AI training use cases. To ensure transparency and compliance, we maintain relevant documentation and have previously shared redacted agreements for selected datasets as evidence of our data rights and licensing authority.
Data Dictionary
| Column Name | Data Type | Description | Possible Values/Notes |
|---|---|---|---|
| Modality | String | Imaging modality | CT |
| Body_Region | String | Anatomical region scanned | Brain, Chest, Abdomen, Pelvis, Spine, Neck, etc. |
| Image_File | String | CT scan image file | .dcm |
| Report_File | String | Radiology findings report | |
| Findings | Text | Radiologist interpretation | Free-text clinical observations |
| Image_Width | Integer | Image width in pixels | Positive integer |
| Image_Height | Integer | Image height in pixels | Positive integer |
Considerations
This dataset is provided for research and educational purposes only. It contains only sample data.
Additional Notes
- The dataset combines CT scan images with corresponding radiology findings, making it suitable for both computer vision and multimodal AI applications.
- All CT images are stored in the industry-standard DICOM format and paired with radiology reports in PDF format for seamless integration into healthcare AI pipelines.
- Ideal for disease detection, image classification, segmentation, report generation, vision-language models, clinical decision support, and medical image analysis.
- The dataset is compatible with PACS systems, DICOM viewers, and leading deep learning frameworks used in medical imaging research.
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£75,000
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