activity
20172022
most citedDeep De-Aliasing for Fast Compressive Sensing MRI

44 citations · 140 across the 22 of their papers we have counts for

collaborators

36 papers

eess.IV2022

Adversarial Transformer for Repairing Human Airway Segmentation

Zeyu Tang, Nan Yang, Simon Walsh +1

Discontinuity in the delineation of peripheral bronchioles hinders the potential clinical application of automated airway segmentation models. Moreover, the deployment of such mode…

eess.IV2022

Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal

Michael Tanzer, Sea Hee Yook, Guang Yang +2

As diffusion tensor imaging (DTI) gains popularity in cardiac imaging due to its unique ability to non-invasively assess the cardiac microstructure, deep learning-based Artificial…

eess.IV20225 cited

ME-Net: Multi-Encoder Net Framework for Brain Tumor Segmentation

Wenbo Zhang, Guang Yang, He Huang +4

Glioma is the most common and aggressive brain tumor. Magnetic resonance imaging (MRI) plays a vital role to evaluate tumors for the arrangement of tumor surgery and the treatment…

eess.IV2022

Unsupervised Image Registration Towards Enhancing Performance and Explainability in Cardiac And Brain Image Analysis

Chengjia Wang, Guang Yang, Giorgos Papanastasiou

Magnetic Resonance Imaging (MRI) typically recruits multiple sequences (defined here as "modalities"). As each modality is designed to offer different anatomical and functional cli…

eess.IV20211 cited

Synthetic Velocity Mapping Cardiac MRI Coupled with Automated Left Ventricle Segmentation

Xiaodan Xing, Yinzhe Wu, David Firmin +2

Temporal patterns of cardiac motion provide important information for cardiac disease diagnosis. This pattern could be obtained by three-directional CINE multi-slice left ventricul…

eess.IV2021

Focal Attention Networks: optimising attention for biomedical image segmentation

Michael Yeung, Leonardo Rundo, Evis Sala +2

In recent years, there has been increasing interest to incorporate attention into deep learning architectures for biomedical image segmentation. The modular design of attention mec…