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PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning (submitted to ISBI 2025)

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PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning

  • Paper: arXiv preprint (submitted to ISBI 2025)

  • Cite:

    @misc{galada2024prismprivacypreservingintersitemri,
        title={PRISM: Privacy-preserving Inter-Site MRI Harmonization via Disentangled Representation Learning}, 
        author={Sarang Galada and Tanurima Halder and Kunal Deo and Ram P Krish and Kshitij Jadhav},
        year={2024},
        eprint={2411.06513},
        archivePrefix={arXiv},
        primaryClass={eess.IV},
        url={https://arxiv.org/abs/2411.06513},
    }

Usage:

  • Preprocessing: To be updated soon
  • Training: Run the PRISM-training notebook in the /code folder separately for each MRI site dataset and save the models
  • Inference: To be updated soon

Architecture:

PRISM Architecture


Results:

Harmonized

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