46 citations · 78 across the 11 of their papers we have counts for
12 papers
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…
Magnetization Transfer-Mediated MR Fingerprinting
Daniel J. West, Gastao Cruz, Rui P. A. G. Teixeira +5
Purpose: Magnetization transfer (MT) and inhomogeneous MT (ihMT) contrasts are used in MRI to provide information about macromolecular tissue content. In particular, MT is sensitiv…
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…
Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation
Ilkay Oksuz, James R. Clough, Bram Ruijsink +6
Segmenting anatomical structures in medical images has been successfully addressed with deep learning methods for a range of applications. However, this success is heavily dependen…
Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space
lkay Oksuz, James Clough, Bram Ruijsink +7
In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corruption of k-space lines, which can result in artefacts in the reconstructed images. In this paper, we propose…
Magnetic Resonance Fingerprinting using Recurrent Neural Networks
Ilkay Oksuz, Gastao Cruz, James Clough +6
Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single,…
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning
Ilkay Oksuz, Bram Ruijsink, Esther Puyol-Anton +8
Good quality of medical images is a prerequisite for the success of subsequent image analysis pipelines. Quality assessment of medical images is therefore an essential activity and…
Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection
Ilkay Oksuz, Bram Ruijsink, Esther Puyol-Anton +6
Quality assessment of medical images is essential for complete automation of image processing pipelines. For large population studies such as the UK Biobank, artefacts such as thos…