33 citations · 61 across the 7 of their papers we have counts for
7 papers
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…
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…
Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis
Hadrien Reynaud, Mengyun Qiao, Mischa Dombrowski +5
Image synthesis is expected to provide value for the translation of machine learning methods into clinical practice. Fundamental problems like model robustness, domain transfer, ca…
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…
Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images
Berke Doga Basaran, Mengyun Qiao, Paul M. Matthews +1
Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In th…
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data
Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu +6
Cardiovascular disease, the leading cause of death globally, is an age-related disease. Understanding the morphological and functional changes of the heart during ageing is a key s…
Fully Automated Left Atrium Cavity Segmentation from 3D GE-MRI by Multi-Atlas Selection and Registration
Mengyun Qiao, Yuanyuan Wang, Rob J. van der Geest +1
This paper presents a fully automated method to segment the complex left atrial (LA) cavity, from 3D Gadolinium-enhanced magnetic resonance imaging (GE-MRI) scans. The proposed met…