InfoBayAI/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 from 2.46 Million+ patients, spanning multiple imaging modalities and healthcare document types including MRI, CT Scan, X-Ray, Ultrasound, Pathology, Electronic Health Records (EHR), HIV ART records, dermatology images, OPD prescriptions, and discharge summaries.

This dataset is designed for developing next-generation healthcare AI systems capable of assisting clinicians, researchers, hospitals, medical device manufacturers, and pharmaceutical organizations.

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Dataset Statistics

Property	Value
Dataset Name	InfoBay.AI Healthcare Imaging Dataset Catalogue
Total Patients	2.46 Million+
Total Files & Images	112 Million+
License	CC BY 4.0
Domain	Medical Imaging & Healthcare
Modalities	MRI, CT, X-Ray, Ultrasound, Pathology, Clinical Documents

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Dataset Breakdown

Record Category	Patients	Files / Images
MRI	167,273	46,849,726 Images
CT Scan	276,113	65,303,386 Images
IPD & IVF Discharge Summaries	552,793	554,845 Files
Dermatology & OPD Prescriptions	444,686	461,467 Images
X-Ray	324,889	559,339 Images
USG & ECHO	4,923	15,948 Images
Pathology	44,868	44,897 Files
Longitudinal EHR Records	131,800	2,877,297 Files
Longitudinal HIV ART	516,691	516,691 Files

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Key Features

• 112 Million+ healthcare files and medical images
• 2.46 Million+ patient records
• Multi-modality imaging dataset
• Clinical healthcare documents
• Longitudinal patient records
• Enterprise-scale medical data
• Suitable for multimodal AI training
• High-resolution medical imaging
• Diverse anatomical coverage
• Real-world clinical data

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Imaging Modalities

The catalogue includes:

• Magnetic Resonance Imaging (MRI)
• Computed Tomography (CT)
• X-Ray Imaging
• Ultrasound (USG)
• Echocardiography (ECHO)
• Digital Pathology
• Dermatology Images
• Clinical Prescription Images
• Medical Reports
• Electronic Health Records
• Longitudinal Patient Records

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Medical Specialties Covered

• Radiology
• Neurology
• Orthopedics
• Oncology
• Cardiology
• Dermatology
• Gastroenterology
• Pulmonology
• Gynecology
• Urology
• Pathology
• Internal Medicine
• Infectious Diseases
• Emergency Medicine

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AI & Research Applications

This dataset is suitable for developing:

• Medical Vision Language Models (VLMs)
• Medical Large Language Models (LLMs)
• Diagnostic AI
• Clinical Decision Support Systems
• Disease Detection Models
• Image Classification
• Image Segmentation
• Organ Detection
• Lesion Detection
• Medical Report Generation
• Vision Question Answering
• Medical OCR
• Retrieval-Augmented Generation (RAG)
• Medical Image Captioning
• Clinical Search Systems
• Medical Knowledge Graphs

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Enterprise Applications

This catalogue can support:

• Hospital AI Platforms
• PACS Integration
• Clinical Decision Support
• Healthcare Analytics
• Medical Imaging Software
• Digital Health Platforms
• Pharmaceutical Research
• Medical Device AI
• Clinical Research
• Medical Education
• Healthcare Data Mining
• Medical Search Engines
• Population Health Analytics

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Supported AI Tasks

• Image Classification
• Object Detection
• Image Segmentation
• Medical Image Retrieval
• Image Captioning
• Vision Language Modeling
• Disease Prediction
• Clinical NLP
• Information Extraction
• Medical Question Answering
• Image Similarity Search
• Foundation Model Training

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Dataset Quality

The dataset consists of real-world healthcare records collected through enterprise healthcare workflows.

Characteristics include:

• High-resolution medical imaging
• Multiple imaging modalities
• Longitudinal patient information
• Diverse patient demographics
• Multiple anatomical regions
• Standard clinical imaging protocols
• Large-scale enterprise data
• Extensive healthcare coverage

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Example Schema

Depending on modality, datasets may contain fields such as:

{
  "patient_id": "string",
  "study_id": "string",
  "series_id": "string",
  "image": "Image",
  "modality": "string",
  "body_part": "string",
  "slice_index": "int64"
}

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Intended Use

The dataset is intended for:

• AI Research
• Academic Research
• Healthcare AI Development
• Foundation Model Training
• Medical Computer Vision
• Biomedical Research
• Clinical Decision Support
• Enterprise AI Solutions
• Benchmarking Medical AI Models

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Data Source

The dataset has been procured through formal agreements and generated during the ordinary course of business.

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Citation

@dataset{infobay_healthcare_catalogue_2026,
  title     = {InfoBay.AI Healthcare Imaging Dataset Catalogue},
  author    = {InfoBay.AI},
  year      = {2026},
  publisher = {InfoBay.AI},
  license   = {CC BY 4.0}
}

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License

This dataset is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

You are free to:

• Share
• Copy
• Redistribute
• Adapt
• Remix
• Build upon the material
• Use commercially

provided that appropriate attribution is given to InfoBay.AI.

License: https://creativecommons.org/licenses/by/4.0/

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Access to Full Dataset

The repository contains representative sample data intended for research and evaluation.

For access to the complete enterprise dataset, commercial licensing, or custom healthcare data solutions, please contact:

InfoBay.AI

• Website: https://infobay.ai
• Email: datareq@infobay.ai
• Phone: +91 8303174762

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Disclaimer

This repository contains sample data for research and evaluation purposes. Users are responsible for ensuring compliance with applicable healthcare regulations, privacy laws, ethical guidelines, and institutional review requirements before using the data in research or commercial applications.

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Acknowledgements

The InfoBay.AI Healthcare Imaging Dataset Catalogue has been curated to accelerate innovation in Medical AI, Diagnostic Imaging, Computer Vision, Biomedical Research, Clinical NLP, Vision Language Models, and Enterprise Healthcare Analytics. By providing one of the largest multimodal healthcare collections, this dataset aims to support the development of safer, more accurate, and clinically useful AI systems.