5 papers
B-FIRE: Binning-Free Diffusion Implicit Neural Representation for Hyper-Accelerated Motion-Resolved MRI
Di Xu, Hengjie Liu, Yang Yang +11
Accelerated dynamic volumetric magnetic resonance imaging (4DMRI) is essential for applications relying on motion resolution. Existing 4DMRI produces acceptable artifacts of averag…
Zero-shot Multi-Contrast Brain MRI Registration by Intensity Randomizing T1-weighted MRI (LUMIR25)
Hengjie Liu, Yimeng Dou, Di Xu +3
In this paper, we present our submission to the LUMIR25 task of Learn2Reg 2025, which ranked 1st overall on the test set. Extended from LUMIR24, this year's task focuses on zero-sh…
Accelerated Patient-specific Non-Cartesian MRI Reconstruction using Implicit Neural Representations
Di Xu, Hengjie Liu, Xin Miao +9
The scanning time for a fully sampled MRI can be undesirably lengthy. Compressed sensing has been developed to minimize image artifacts in accelerated scans, but the required itera…
Rapid Reconstruction of Extremely Accelerated Liver 4D MRI via Chained Iterative Refinement
Di Xu, Xin Miao, Hengjie Liu +8
Abstract Purpose: High-quality 4D MRI requires an impractically long scanning time for dense k-space signal acquisition covering all respiratory phases. Accelerated sparse sampling…
TomoGRAF: A Robust and Generalizable Reconstruction Network for Single-View Computed Tomography
Di Xu, Yang Yang, Hengjie Liu +4
Computed tomography (CT) provides high spatial resolution visualization of 3D structures for scientific and clinical applications. Traditional analytical/iterative CT reconstructio…