4 citations · 15 across the 6 of their papers we have counts for
6 papers
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
Che Liu, Zhongwei Wan, Cheng Ouyang +3
Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) method…
T3D: Advancing 3D Medical Vision-Language Pre-training by Learning Multi-View Visual Consistency
Che Liu, Cheng Ouyang, Yinda Chen +7
While 3D visual self-supervised learning (vSSL) shows promising results in capturing visual representations, it overlooks the clinical knowledge from radiology reports. Meanwhile,…
G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
Che Liu, Cheng Ouyang, Sibo Cheng +3
Recently, medical vision-language pre-training (VLP) has reached substantial progress to learn global visual representation from medical images and their paired radiology reports.…
IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training
Che Liu, Sibo Cheng, Miaojing Shi +3
In the field of medical Vision-Language Pre-training (VLP), significant efforts have been devoted to deriving text and image features from both clinical reports and associated medi…
Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images
Che Liu, Anand Shah, Wenjia Bai +1
Medical Vision-Language Pre-training (VLP) learns representations jointly from medical images and paired radiology reports. It typically requires large-scale paired image-text data…
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…