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Author

Charles Millard

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Open access Jun 2026

Optimized Multi-Contrast Self-Supervised MRI Reconstruction Using Learned K-Space Partitioning

This work proposes a multi-contrast self-supervised multi-contrast learned partitioning method that jointly trains on multiple under-sampled contrasts without requiring fully sampled k-space data as a reference, and improves reconstruction fidelity over single-contrast self-supervised MRI reconstructions.

Brenden T. Kadota, Charles Millard, Mark Chiew · 0 citations

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