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Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and
Oliver Diaz1, Kaisar Kushibar1, Richard Osuala1
1Faculty of Mathematics and Computer Science, University of Barcelona, Barcelona, Spain.
Preparing medical images is crucial for artificial intelligence (AI) in healthcare. This guide outlines essential steps like de-identification, curation, and annotation for robust AI development in medical imaging.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Data Science
Background:
- Medical imaging generates vast data, necessitating advanced solutions like artificial intelligence (AI).
- Reliable AI development hinges on meticulously prepared medical image data.
- AI promises to transform clinical practice and medical research.
Purpose of the Study:
- To provide a comprehensive guide on preparing medical images for AI applications.
- To review available tools and repositories for medical image preparation and storage.
Main Methods:
- Image acquisition
- Patient data de-identification
- Data curation and quality control
- Secure image storage
- Image annotation
Main Results:
- A detailed pipeline for medical image preparation is presented.
- A review of open-access tools for each preparation step is provided.
- Key medical image repositories for various organs and diseases are highlighted.
Conclusions:
- Standardized medical image preparation is essential for effective AI implementation.
- The availability of tools and repositories supports the advancement of AI in medical imaging.
- Future directions in medical image preparation for AI are discussed.
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