36 citations · 61 across the 8 of their papers we have counts for
5 papers · 1 filter
Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics
Ziyu Ni, Linda Wei, Lijian Xu +4
Local hemodynamic forces play an important role in determining the functional significance of coronary arterial stenosis and understanding the mechanism of coronary disease progres…
Towards Self-supervised and Weight-preserving Neural Architecture Search
Zhuowei Li, Yibo Gao, Zhenzhou Zha +4
Neural architecture search (NAS) algorithms save tremendous labor from human experts. Recent advancements further reduce the computational overhead to an affordable level. However,…
Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
Zhuowei Li, Zihao Liu, Zhiqiang Hu +5
Medical image segmentation has been widely recognized as a pivot procedure for clinical diagnosis, analysis, and treatment planning. However, the laborious and expensive annotation…
Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation
Jinxi Xiang, Zhuowei Li, Wenji Wang +2
Deep learning has demonstrated significant improvements in medical image segmentation using a sufficiently large amount of training data with manual labels. Acquiring well-represen…
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…