11 papers
Is Deformable Image Registration Ready for Brain Metastasis Reirradiation Dose Accumulation? A Longitudinal MRI Benchmark of Registration Accuracy
Hengjie Liu, Manju Sharma, Xinyi Fu +2
Dose accumulation is increasingly important in adaptive radiation therapy and reirradiation, but its clinical validity depends on the performance of deformable image registration (…
The Right Prior for the Right Deformation: Rethinking Continuous Deformable Image Registration
Hengjie Liu, Chushu Shen, Dan Ruan +1
Deformable image registration models implicitly encode deformation priors through their parametrization and optimization. In this work, we conduct a validation study on continuous…
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…
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…
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…
Exploring Automated Contouring Across Institutional Boundaries: A Deep Learning Approach with Mouse Micro-CT Datasets
Lu Jiang, Di Xu, Qifan Xu +4
Image-guided mouse irradiation is essential to understand interventions involving radiation prior to human studies. Our objective is to employ Swin UNEt Transformers (Swin UNETR) t…
Paired Conditional Generative Adversarial Network for Highly Accelerated Liver 4D MRI
Di Xu, Xin Miao, Hengjie Liu +8
Purpose: 4D MRI with high spatiotemporal resolution is desired for image-guided liver radiotherapy. Acquiring densely sampling k-space data is time-consuming. Accelerated acquisiti…
A Two-Step Framework for Multi-Material Decomposition of Dual Energy Computed Tomography from Projection Domain
Di Xu, Qihui Lyu, Dan Ruan +1
Dual-energy computed tomography (DECT) utilizes separate X-ray energy spectra to improve multi-material decomposition (MMD) for various diagnostic applications. However accurate de…
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer
Di Xu, Hengjie Liu, Dan Ruan +1
Dynamic magnetic resonance imaging (DMRI) is an effective imaging tool for diagnosis tasks that require motion tracking of a certain anatomy. To speed up DMRI acquisition, k-space…