Tan Z, Liebig PA, Hofmann A, Laun FB, Knoll F (2026)
Publication Type: Journal article
Publication year: 2026
DOI: 10.1002/mrm.70250
Purpose: High-resolution diffusion-weighted imaging (DWI) is clinically demanding. The purpose of this work is to develop an efficient self-supervised algorithm unrolling technique for submillimeter-resolution DWI. Methods: We developed submillimeter DWI acquisition utilizing multi-band multi-shot EPI with diffusion shift encoding. We unrolled the alternating direction method of multipliers (ADMM) to perform scan-specific self-gated self-supervised DeepDWI learning for multi-shot echo planar imaging with diffusion shift encoding on a clinical 7 T scanner. Results: We demonstrate that (1) ADMM unrolling is generalizable across slices, (2) ADMM unrolling outperforms multiplexed sensitivity-encoding (MUSE) and compressed sensing with locally-low rank (LLR) regularization in terms of image sharpness, tissue continuity, and motion robustness, and (3) ADMM unrolling enables clinically feasible inference time. Conclusion: Our proposed ADMM unrolling enables whole brain DWI of 21 diffusion volumes at 0.7 mm isotropic resolution and 10 min scan, and shows higher signal-to-noise ratio (SNR), clearer tissue delineation, and improved motion robustness, which makes it plausible for clinical translation.
APA:
Tan, Z., Liebig, P.A., Hofmann, A., Laun, F.B., & Knoll, F. (2026). High-Resolution Diffusion-Weighted Imaging With Self-Gated Self-Supervised Unrolled Reconstruction. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.70250
MLA:
Tan, Zhengguo, et al. "High-Resolution Diffusion-Weighted Imaging With Self-Gated Self-Supervised Unrolled Reconstruction." Magnetic Resonance in Medicine (2026).
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