44 citations · 183 across the 24 of their papers we have counts for
12 papers · 1 filter
MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks
Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +3
In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand…
Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge
Xiahai Zhuang, Lei Li, Christian Payer +31
Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable…
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)…
Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models
Nathan J Olliverre, Guang Yang, Gregory Slabaugh +2
Magnetic Resonance Spectroscopy (MRS) provides valuable information to help with the identification and understanding of brain tumors, yet MRS is not a widely available medical ima…