RadHarmony library simplifies AI integration for radiological data

A new open-source Python library called RadHarmony has been developed to streamline the process of handling diverse radiological datasets for deep learning applications. It offers a unified API for loading, harmonizing, and augmenting data, supporting various label types and imaging modalities like chest X-rays, CT, and MRI. The library standardizes metadata from numerous public datasets and integrates with MONAI for efficient data delivery, while also featuring an AI-agent skill to guide users through dataset integration. RadHarmony was used to pretrain a vision transformer model, RadHarmony-ViT, demonstrating its utility in combining heterogeneous datasets without requiring dataset-specific code. AI

IMPACT Streamlines AI model development for medical imaging by simplifying data integration and harmonization.

RANK_REASON Publication of a research paper detailing a new open-source library for AI data handling. [lever_c_demoted from research: ic=1 ai=1.0]

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• alphaXiv
• arXiv
• CatalyzeX
• DagsHub
• Gotit.pub
• Hugging Face
• Monai
• Python
• RadHarmony
• RadHarmony-ViT
• ScienceCast

• paper
• infra
• product

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