6 papers · 1 filter
MedQ-Engine: A Closed-Loop Data Engine for Evolving MLLMs in Medical Image Quality Assessment
Jiyao Liu, Junzhi Ning, Wanying Qu +4
Medical image quality assessment (Med-IQA) is a prerequisite for clinical AI deployment, yet multimodal large language models (MLLMs) still fall substantially short of human expert…
MedQ-UNI: Toward Unified Medical Image Quality Assessment and Restoration via Vision-Language Modeling
Jiyao Liu, Junzhi Ning, Wanying Qu +4
Existing medical image restoration (Med-IR) methods are typically modality-specific or degradation-specific, failing to generalize across the heterogeneous degradations encountered…
SurgVidLM: Towards Multi-grained Surgical Video Understanding with Large Language Model
Guankun Wang, Junyi Wang, Wenjin Mo +11
Surgical scene understanding is critical for surgical training and robotic decision-making in robot-assisted surgery. Recent advances in Multimodal Large Language Models (MLLMs) ha…
HyperST: Hierarchical Hyperbolic Learning for Spatial Transcriptomics Prediction
Chen Zhang, Yilu An, Ying Chen +7
Spatial Transcriptomics (ST) merges the benefits of pathology images and gene expression, linking molecular profiles with tissue structure to analyze spot-level function comprehens…
F^2TTA: Free-Form Test-Time Adaptation on Cross-Domain Medical Image Classification via Image-Level Disentangled Prompt Tuning
Wei Li, Jingyang Zhang, Lihao Liu +4
Test-Time Adaptation (TTA) has emerged as a promising solution for adapting a source model to unseen medical sites using unlabeled test data, due to the high cost of data annotatio…
Building a Human-Verified Clinical Reasoning Dataset via a Human LLM Hybrid Pipeline for Trustworthy Medical AI
Chao Ding, Mouxiao Bian, Pengcheng Chen +11
Despite strong performance in medical question-answering, the clinical adoption of Large Language Models (LLMs) is critically hampered by their opaque 'black-box' reasoning, limiti…