activity
20172026
most citedFully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI

58 citations · 173 across the 29 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

eess.IV2020★ 3 cited

Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint

Chenyu Liu, Wangbin Ding, Lei Li +4

Delineating the brain tumor from magnetic resonance (MR) images is critical for the treatment of gliomas. However, automatic delineation is challenging due to the complex appearanc…

cs.CV2020

Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks

Wangbin Ding, Lei Li, Xiahai Zhuang +1

Both image registration and label fusion in the multi-atlas segmentation (MAS) rely on the intensity similarity between target and atlas images. However, such similarity can be pro…

eess.IV2020★ 5 cited

AtrialJSQnet: A New Framework for Joint Segmentation and Quantification of Left Atrium and Scars Incorporating Spatial and Shape Information

Lei Li, Veronika A. Zimmer, Julia A. Schnabel +1

Left atrial (LA) and atrial scar segmentation from late gadolinium enhanced magnetic resonance imaging (LGE MRI) is an important task in clinical practice. %, to guide ablation the…

eess.IV2020★ 4 cited

Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention

Lei Li, Xin Weng, Julia A. Schnabel +1

We propose an end-to-end deep neural network (DNN) which can simultaneously segment the left atrial (LA) cavity and quantify LA scars. The framework incorporates the continuous spa…

eess.IV2020★ 10 cited

Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge

Xiahai Zhuang, Jiahang Xu, Xinzhe Luo +20

Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suff…