870 citations · 2.4k across the 62 of their papers we have counts for
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T1/T2 relaxation temporal modelling from accelerated acquisitions using a Latent Transformer
Fanwen Wang, Michael Tanzer, Mengyun Qiao +4
Quantitative cardiac magnetic resonance T1 and T2 mapping enable myocardial tissue characterisation but the lengthy scan times restrict their widespread clinical application. We pr…
DeepMesh: Mesh-based Cardiac Motion Tracking using Deep Learning
Qingjie Meng, Wenjia Bai, Declan P O'Regan +1
3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardiovascular diseases. Current sta…
CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction
Chengyan Wang, Jun Lyu, Shuo Wang +25
Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patien…
LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation
Berke Doga Basaran, Weitong Zhang, Mengyun Qiao +3
Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spat…
Hierarchical Uncertainty Estimation for Medical Image Segmentation Networks
Xinyu Bai, Wenjia Bai
Learning a medical image segmentation model is an inherently ambiguous task, as uncertainties exist in both images (noise) and manual annotations (human errors and bias) used for m…
M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization
Che Liu, Sibo Cheng, Chen Chen +5
Medical vision-language models enable co-learning and integrating features from medical imaging and clinical text. However, these models are not easy to train and the latent repres…
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy
Mengyun Qiao, Shuo Wang, Huaqi Qiu +4
Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical facto…