10 papers
HyDAR-Pano3D: A Hybrid Disentangled Anatomical Recovery Framework for Panoramic-to-3D Reconstruction
Yaoyao Yue, Jérôme Schmid, Xiaoshuang Li +2
Panoramic radiograph (PR) is fundamentally used in routine dental care, but it inherently provides only a two-dimensional (2D) projection of complex three-dimensional (3D) craniofa…
CBT-Audio: Evaluating Audio Language Models for Patient-Side Distress Intensity Estimation in CBT Session Recordings
Qixuan Hu, Shuchang Ye, Xumou Zhang +8
Cognitive behavioural therapy is widely used to help patients understand and manage psychological distress. It is often delivered through spoken conversation, where therapists atte…
RadGenome-Anatomy: A Large-Scale Anatomy-Labeled Chest Radiograph Dataset via Physically Grounded Volumetric Projection
Shuchang Ye, Mingyuan Meng, Hao Wang +2
Anatomical structure labels for chest radiographs are essential for medical image segmentation and a broad range of downstream diagnostic tasks. However, annotating anatomy directl…
Intersectional Fairness in Vision-Language Models for Medical Image Disease Classification
Yupeng Zhang, Adam G. Dunn, Usman Naseem +1
Medical artificial intelligence (AI) systems, particularly multimodal vision-language models (VLM), often exhibit intersectional biases where models are systematically less confide…
MRG-R1: Reinforcement Learning for Clinically Aligned Medical Report Generation
Pengyu Wang, Shuchang Ye, Usman Naseem +1
Medical report generation aims to automatically produce radiology-style reports from medical images, supporting efficient and accurate clinical decision-making.However, existing ap…
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic Approximation
Shuchang Ye, Usman Naseem, Mingyuan Meng +1
Medical language-guided segmentation, integrating textual clinical reports as auxiliary guidance to enhance image segmentation, has demonstrated significant improvements over unimo…
MRGAgents: A Multi-Agent Framework for Improved Medical Report Generation with Med-LVLMs
Pengyu Wang, Shuchang Ye, Usman Naseem +1
Medical Large Vision-Language Models (Med-LVLMs) have been widely adopted for medical report generation. Despite Med-LVLMs producing state-of-the-art performance, they exhibit a bi…
MAISY: Motion-Aware Image SYnthesis for Medical Image Motion Correction
Andrew Zhang, Hao Wang, Shuchang Ye +2
Patient motion during medical image acquisition causes blurring, ghosting, and distorts organs, which makes image interpretation challenging. Current state-of-the-art algorithms us…
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets
Yongpei Ma, Pengyu Wang, Adam Dunn +2
Medical Visual Question Answering (MVQA) systems can interpret medical images in response to natural language queries. However, linguistic variability in question phrasing often un…
Med-R2: Perception and Reflection-driven Complex Reasoning for Medical Report Generation
Hao Wang, Shuchang Ye, Jinghao Lin +2
Automated medical report generation (MRG) is increasingly used to reduce the burden of manual reporting and for decision support. Large vision-language models (LVLMs) hold great pr…