9 citations · 10 across the 13 of their papers we have counts for
8 papers · 1 filter
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…
SPIDER: Structure-Preferential Implicit Deep Network for Biplanar X-ray Reconstruction
Tianqi Yu, Xuanyu Tian, Jiawen Yang +4
Biplanar X-ray imaging is widely used in health screening, postoperative rehabilitation evaluation of orthopedic diseases, and injury surgery due to its rapid acquisition, low radi…
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…
Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation
Qing Wu, Chenhe Du, Xuanyu Tian +3
Motion correction (MoCo) in radial MRI is a particularly challenging problem due to the unpredictability of subject movement. Current state-of-the-art (SOTA) MoCo algorithms often…
Zero-Shot Image Denoising for High-Resolution Electron Microscopy
Xuanyu Tian, Zhuoya Dong, Xiyue Lin +5
High-resolution electron microscopy (HREM) imaging technique is a powerful tool for directly visualizing a broad range of materials in real-space. However, it faces challenges in d…
DPER: Diffusion Prior Driven Neural Representation for Limited Angle and Sparse View CT Reconstruction
Chenhe Du, Xiyue Lin, Qing Wu +9
Limited-angle and sparse-view computed tomography (LACT and SVCT) are crucial for expanding the scope of X-ray CT applications. However, they face challenges due to incomplete data…
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…
Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image
Xuanyu Tian, Qing Wu, Hongjiang Wei +1
Fluorescence microscopy is a key driver to promote discoveries of biomedical research. However, with the limitation of microscope hardware and characteristics of the observed sampl…