13 citations · 31 across the 3 of their papers we have counts for
5 papers
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging
Zhaohan Xiong, Qing Xia, Zhiqiang Hu +41
Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial fir…
Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors
Qian Yue, Xinzhe Luo, Qing Ye +2
Cardiac segmentation from late gadolinium enhancement MRI is an important task in clinics to identify and evaluate the infarction of myocardium. The automatic segmentation is howev…
Atrial Scar Quantification via Multi-scale CNN in the Graph-cuts Framework
Lei Li, Fuping Wu, Guang Yang +6
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the…
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)…