58 citations · 171 across the 20 of their papers we have counts for
9 papers · 1 filter
HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis
Xiaodan Xing, Javier Del Ser, Yinzhe Wu +6
Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part of digital healthcare twins is…
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis
Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò +6
Compressed sensing (CS) has been playing a key role in accelerating the magnetic resonance imaging (MRI) acquisition process. With the resurgence of artificial intelligence, deep n…
Synthetic Velocity Mapping Cardiac MRI Coupled with Automated Left Ventricle Segmentation
Xiaodan Xing, Yinzhe Wu, David Firmin +2
Temporal patterns of cardiac motion provide important information for cardiac disease diagnosis. This pattern could be obtained by three-directional CINE multi-slice left ventricul…
Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data
Jun Chen, Heye Zhang, Raad Mohiaddin +4
Semi-supervised learning provides great significance in left atrium (LA) segmentation model learning with insufficient labelled data. Generalising semi-supervised learning to cross…
Recent Advances in Fibrosis and Scar Segmentation from Cardiac MRI: A State-of-the-Art Review and Future Perspectives
Yinzhe Wu, Zeyu Tang, Binghuan Li +2
Segmentation of cardiac fibrosis and scar are essential for clinical diagnosis and can provide invaluable guidance for the treatment of cardiac diseases. Late Gadolinium enhancemen…
JAS-GAN: Generative Adversarial Network Based Joint Atrium and Scar Segmentations on Unbalanced Atrial Targets
Jun Chen, Guang Yang, Habib Khan +7
Automated and accurate segmentations of left atrium (LA) and atrial scars from late gadolinium-enhanced cardiac magnetic resonance (LGE CMR) images are in high demand for quantifyi…
Three-Dimensional Embedded Attentive RNN (3D-EAR) Segmentor for Left Ventricle Delineation from Myocardial Velocity Mapping
Mengmeng Kuang, Yinzhe Wu, Diego Alonso-Álvarez +4
Myocardial Velocity Mapping Cardiac MR (MVM-CMR) can be used to measure global and regional myocardial velocities with proved reproducibility. Accurate left ventricle delineation i…
Automated Multi-Channel Segmentation for the 4D Myocardial Velocity Mapping Cardiac MR
Yinzhe Wu, Suzan Hatipoglu, Diego Alonso-Álvarez +4
Four-dimensional (4D) left ventricular myocardial velocity mapping (MVM) is a cardiac magnetic resonance (CMR) technique that allows assessment of cardiac motion in three orthogona…
Simultaneous Left Atrium Anatomy and Scar Segmentations via Deep Learning in Multiview Information with Attention
Guang Yang, Jun Chen, Zhifan Gao +13
Three-dimensional late gadolinium enhanced (LGE) cardiac MR (CMR) of left atrial scar in patients with atrial fibrillation (AF) has recently emerged as a promising technique to str…