5 citations · 6 across the 4 of their papers we have counts for
4 papers
Towards a Unified Theoretical Framework for Splitting-based Self-Supervised MRI Reconstruction
Siying Xu, Kerstin Hammernik, Daniel Rueckert +2
The demand for high-resolution, non-invasive imaging continues to drive innovation in magnetic resonance imaging (MRI), but long acquisition times remain a major practical limitati…
Self-supervised feature learning for cardiac Cine MR image reconstruction
Siying Xu, Marcel Früh, Kerstin Hammernik +6
We propose a self-supervised feature learning assisted reconstruction (SSFL-Recon) framework for MRI reconstruction to address the limitation of existing supervised learning method…
Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imaging
Wenqi Huang, Veronika Spieker, Siying Xu +6
Conventional cardiac cine MRI methods rely on retrospective gating, which limits temporal resolution and the ability to capture continuous cardiac dynamics, particularly in patient…
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging
Siying Xu, Kerstin Hammernik, Andreas Lingg +5
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, w…