46 citations · 48 across the 5 of their papers we have counts for
10 papers
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…