Author

Jing-Ran Xu

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Sep 2026

NL-TINR: implicit neural representation based nonlocal functional tensor decomposition for zero-shot 3D multi-contrast MRI reconstruction.

OBJECTIVE 3D quantitative magnetic resonance imaging (qMRI) enables noninvasive tissue characterization but often requires prolonged acquisition times for multi-contrast imaging, limiting its broader clinical adoption. Although deep learning has shown promise for accelerated MRI reconstruction, supervised methods rely...

Jing-Ran Xu, Seng Jia, Yuan-Biao Yang et al. · Physics in Medicine and Biol... · 0 citations

Preprint Sep 2026

SGAM: Shared Gaussian Geometry with Implicit Amplitude Modeling for Scan-Specific 3D Multi-Contrast MRI Reconstruction

Three-dimensional (3D) multi-contrast magnetic resonance imaging (MCMRI) provides rich anatomical and quantitative information but requires long acquisition times, motivating k-space undersampling. However, reconstruction of large volumetric datasets imposes substantial computational and memory demands. To address this...

Jing-Ran Xu, Dong Liang, Hai-Rong Zheng et al. · 0 citations

Aug 2026

Unsupervised Dynamic MRI Reconstruction via Low-Rank Patch-Based Tensor Functions with Implicit Neural Representation.

TenF-INR is proposed, a novel unsupervised framework that integrates low-rank tensor modeling with INR, where each factor matrix in the tensor decomposition is modeled as a learnable factor function within a low-rank decomposition, reducing the parameter space and computational burden.

Yuan-Yuan Liu, Yuan-Biao Yang, Jing Cheng et al. · IEEE journal of biomedical a... · 1 citation