30 citations · 114 across the 30 of their papers we have counts for
8 papers · 1 filter
M3Ret: Unleashing Zero-shot Multimodal Medical Image Retrieval via Self-Supervision
Che Liu, Zheng Jiang, Chengyu Fang +5
Medical image retrieval is essential for clinical decision-making and translational research, relying on discriminative visual representations. Yet, current methods remain fragment…
Knowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding
Jun Li, Che Liu, Wenjia Bai +4
In this work, we address the problem of grounding abnormalities in medical images, where the goal is to localize clinical findings based on textual descriptions. While generalist V…
Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming
Jiazhen Pan, Bailiang Jian, Paul Hager +19
Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static…
How Far Have Medical Vision-Language Models Come? A Comprehensive Benchmarking Study
Che Liu, Jiazhen Pan, Weixiang Shen +3
Vision-Language Models (VLMs) trained on web-scale corpora excel at natural image tasks and are increasingly repurposed for healthcare; however, their competence in medical tasks r…
BOTM: Echocardiography Segmentation via Bi-directional Optimal Token Matching
Zhihua Liu, Lei Tong, Xilin He +4
Existed echocardiography segmentation methods often suffer from anatomical inconsistency challenge caused by shape variation, partial observation and region ambiguity with similar…
Enhancing Abnormality Grounding for Vision Language Models with Knowledge Descriptions
Jun Li, Che Liu, Wenjia Bai +3
Visual Language Models (VLMs) have demonstrated impressive capabilities in visual grounding tasks. However, their effectiveness in the medical domain, particularly for abnormality…
Knowledge-enhanced Multimodal ECG Representation Learning with Arbitrary-Lead Inputs
Che Liu, Cheng Ouyang, Zhongwei Wan +3
Recent advances in multimodal ECG representation learning center on aligning ECG signals with paired free-text reports. However, suboptimal alignment persists due to the complexity…
SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning
Mingsheng Cai, Jiuming Jiang, Wenhao Huang +2
Cardiovascular diseases are a leading cause of death and disability worldwide. Electrocardiogram (ECG) is critical for diagnosing and monitoring cardiac health, but obtaining large…