10 citations · 49 across the 12 of their papers we have counts for
7 papers · 1 filter
Unsupervised Tissue Segmentation via Deep Constrained Gaussian Network
Yang Nan, Peng Tang, Guyue Zhang +5
Tissue segmentation is the mainstay of pathological examination, whereas the manual delineation is unduly burdensome. To assist this time-consuming and subjective manual step, rese…
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…
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…
Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness
Yifeng Guo, Chengjia Wang, Heye Zhang +1
The performance of traditional compressive sensing-based MRI (CS-MRI) reconstruction is affected by its slow iterative procedure and noise-induced artefacts. Although many deep lea…
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…
Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation
Ming Li, Weiwei Zhang, Guang Yang +5
Multi-view echocardiographic sequences segmentation is crucial for clinical diagnosis. However, this task is challenging due to limited labeled data, huge noise, and large gaps acr…
Direct Quantification for Coronary Artery Stenosis Using Multiview Learning
Dong Zhang, Guang Yang, Shu Zhao +3
The quantification of the coronary artery stenosis is of significant clinical importance in coronary artery disease diagnosis and intervention treatment. It aims to quantify the mo…