58 citations · 76 across the 9 of their papers we have counts for
4 papers · 1 filter
Atrial scars segmentation via potential learning in the graph-cuts framework
Lei Li, Fuping Wu, Guang Yang +6
Late Gadolinium Enhancement Magnetic Resonance Imaging (LGE MRI) emerged as a routine scan for patients with atrial fibrillation (AF). However, due to the low image quality automat…
Atrial fibrosis quantification based on maximum likelihood estimator of multivariate images
Fuping Wu, Lei Li, Guang Yang +6
We present a fully-automated segmentation and quantification of the left atrial (LA) fibrosis and scars combining two cardiac MRIs, one is the target late gadolinium-enhanced (LGE)…
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
Maximilian Seitzer, Guang Yang, Jo Schlemper +9
Deep learning approaches have shown promising performance for compressed sensing-based Magnetic Resonance Imaging. While deep neural networks trained with mean squared error (MSE)…
Multiview Two-Task Recursive Attention Model for Left Atrium and Atrial Scars Segmentation
Jun Chen, Guang Yang, Zhifan Gao +9
Late Gadolinium Enhanced Cardiac MRI (LGE-CMRI) for detecting atrial scars in atrial fibrillation (AF) patients has recently emerged as a promising technique to stratify patients,…