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20222026
most citedSpatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction

37 citations · 50 across the 9 of their papers we have counts for

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7 papers · 1 filter

eess.IV2025

Unsupervised Motion-Compensated Decomposition for Cardiac MRI Reconstruction via Neural Representation

Xuanyu Tian, Lixuan Chen, Qing Wu +4

Cardiac magnetic resonance (CMR) imaging is widely used to characterize cardiac morphology and function. To accelerate CMR imaging, various methods have been proposed to recover hi…

eess.IV2025★ 2 cited

SUFFICIENT: A scan-specific unsupervised deep learning framework for high-resolution 3D isotropic fetal brain MRI reconstruction

Jiangjie Wu, Lixuan Chen, Zhenghao Li +6

High-quality 3D fetal brain MRI reconstruction from motion-corrupted 2D slices is crucial for clinical diagnosis. Reliable slice-to-volume registration (SVR)-based motion correctio…

eess.IV2025

Unsupervised Self-Prior Embedding Neural Representation for Iterative Sparse-View CT Reconstruction

Xuanyu Tian, Lixuan Chen, Qing Wu +4

Emerging unsupervised implicit neural representation (INR) methods, such as NeRP, NeAT, and SCOPE, have shown great potential to address sparse-view computed tomography (SVCT) inve…

eess.IV2023

JSMoCo: Joint Coil Sensitivity and Motion Correction in Parallel MRI with a Self-Calibrating Score-Based Diffusion Model

Lixuan Chen, Xuanyu Tian, Jiangjie Wu +4

Magnetic Resonance Imaging (MRI) stands as a powerful modality in clinical diagnosis. However, it is known that MRI faces challenges such as long acquisition time and vulnerability…

eess.IV2023★ 8 cited

Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction

Qing Wu, Lixuan Chen, Ce Wang +4

Emerging neural reconstruction techniques based on tomography (e.g., NeRF, NeAT, and NeRP) have started showing unique capabilities in medical imaging. In this work, we present a n…

eess.IV2023★ 37 cited

Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction

Jie Feng, Ruimin Feng, Qing Wu +3

Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. H…

eess.IV2022

Continuous longitudinal fetus brain atlas construction via implicit neural representation

Lixuan Chen, Jiangjie Wu, Qing Wu +2

Longitudinal fetal brain atlas is a powerful tool for understanding and characterizing the complex process of fetus brain development. Existing fetus brain atlases are typically co…