46 citations · 68 across the 7 of their papers we have counts for
8 papers · 1 filter
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…
Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging
Wenqi Huang, Hongwei Li, Jiazhen Pan +3
In this work, we propose a novel image reconstruction framework that directly learns a neural implicit representation in k-space for ECG-triggered non-Cartesian Cardiac Magnetic Re…
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
Inês P. Machado, Esther Puyol-Antón, Kerstin Hammernik +10
Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decade…
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data
Ines Machado, Esther Puyol-Anton, Kerstin Hammernik +8
Cine cardiac MRI is routinely acquired for the assessment of cardiac health, but the imaging process is slow and typically requires several breath-holds to acquire sufficient k-spa…
LAPNet: Non-rigid Registration derived in k-space for Magnetic Resonance Imaging
Thomas Küstner, Jiazhen Pan, Haikun Qi +7
Physiological motion, such as cardiac and respiratory motion, during Magnetic Resonance (MR) image acquisition can cause image artifacts. Motion correction techniques have been pro…
Channel Attention Networks for Robust MR Fingerprinting Matching
Refik Soyak, Ebru Navruz, Eda Ozgu Ersoy +5
Magnetic Resonance Fingerprinting (MRF) enables simultaneous mapping of multiple tissue parameters such as T1 and T2 relaxation times. The working principle of MRF relies on varyin…