7 papers
HarMoE: Multi-Source Chest Radiograph Pretraining with Dataset-Disentangled Experts
Haozhe Luo, Ziyu Zhou, Shelley Zixin Shu +1
Recent vision-language models for chest X-ray understanding are largely built on image-report alignment and therefore rely heavily on MIMIC-CXR as the dominant pretraining source.…
TCLA: Training-Free Class-wise Logit Adaptation for Medical Vision-Language Models
Tianyou Jiang, Ziyu Zhou
Medical Vision-Language Models (VLMs) exhibit strong zero-shot performance, yet their effectiveness still declines on out-of-distribution (OOD) data due to domain shifts and class…
KEPIL: Knowledge-Enhanced Prompt-Image Learning for Prompt-Robust Disease Detection
Haozhe Luo, Shelley Zixin Shu, Ziyu Zhou +2
Vision--language models (VLMs) show promise for clinical decision support in radiology because they enable joint reasoning over radiological images and clinical text, thereby lever…
Lamps: Learning Anatomy from Multiple Perspectives via Self-supervision in Chest Radiographs
Ziyu Zhou, Haozhe Luo, Mohammad Reza Hosseinzadeh Taher +4
Foundation models have been successful in natural language processing and computer vision because they are capable of capturing the underlying structures (foundation) of natural la…
XBench: A Comprehensive Benchmark for Visual-Language Explanations in Chest Radiography
Haozhe Luo, Shelley Zixin Shu, Ziyu Zhou +2
Vision-language models (VLMs) have recently shown remarkable zero-shot performance in medical image understanding, yet their grounding ability, the extent to which textual concepts…
On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical Imaging
Haozhe Luo, Ziyu Zhou, Zixin Shu +3
Deep neural networks excel in medical imaging but remain prone to biases, leading to fairness gaps across demographic groups. We provide the first systematic exploration of Human-A…