ArticleMagnetic resonance in medicine2026
High-Resolution Diffusion-Weighted Imaging With Self-Gated Self-Supervised Unrolled Reconstruction.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Combined ADC and TMagnetic resonance in medicine · 2026Article
- A Deep Nonlinear Subspace Modeling and Reconstruction for Diffusion-Weighted Imaging Using Denoising Auto-Encoder.Magnetic resonance in medicine · 2026Article
- Joint Reconstruction of Multiple b-Values and Multiple Directions for Accelerating Diffusion Kurtosis Imaging.Magnetic resonance in medicine · 2026Article
- Self-Supervised Deep Learning Framework for Rician Distribution Based Denoising and Modeling of Multi-b Prostate Diffusion MRI.Magnetic resonance in medicine · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
purposeHigh-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.
methodsWe 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.
resultsWe 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.
conclusionOur 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.
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