Deep Learning‐Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization

Background “Batch effect” in MR images, due to vendor‐specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. Purpose We aim to develop a DL model using contrast adjustment and super‐resolution to reduce diffu...

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