activity
20182021
most citedAdaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data

10 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2021★ 10 cited

Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data

Jun Chen, Heye Zhang, Raad Mohiaddin +4

Semi-supervised learning provides great significance in left atrium (LA) segmentation model learning with insufficient labelled data. Generalising semi-supervised learning to cross…

eess.IV2021★ 1 cited

JAS-GAN: Generative Adversarial Network Based Joint Atrium and Scar Segmentations on Unbalanced Atrial Targets

Jun Chen, Guang Yang, Habib Khan +7

Automated and accurate segmentations of left atrium (LA) and atrial scars from late gadolinium-enhanced cardiac magnetic resonance (LGE CMR) images are in high demand for quantifyi…

eess.IV2020★ 4 cited

Simultaneous Left Atrium Anatomy and Scar Segmentations via Deep Learning in Multiview Information with Attention

Guang Yang, Jun Chen, Zhifan Gao +13

Three-dimensional late gadolinium enhanced (LGE) cardiac MR (CMR) of left atrial scar in patients with atrial fibrillation (AF) has recently emerged as a promising technique to str…

cs.LG2019★ 1 cited

Discriminative Consistent Domain Generation for Semi-supervised Learning

Jun Chen, Heye Zhang, Yanping Zhang +6

Deep learning based task systems normally rely on a large amount of manually labeled training data, which is expensive to obtain and subject to operator variations. Moreover, it do…

cs.CV2018★ 4 cited

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,…