90 citations · 240 across the 18 of their papers we have counts for
5 papers · 1 filter
Sparse Concept Channels in Frozen 3D CT Vision Encoders
Farhad Nooralahzadeh, Lea Bogensperger, Christian Bluethgen +1
Large vision-language models are becoming increasingly dominant in 3D medical image interpretation, but we rarely know <i>which</i> internal units encode clinical findings or <i>wh…
CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs
Sergios Gatidis, Curtis Langlotz, Christian Bluethgen
Vision-language models (VLMs) pretrained on large-scale image-text pairs demonstrate strong image-level understanding, but are primarily optimized for global alignment and do not e…
RadAgent: A tool-using AI agent for stepwise interpretation of chest computed tomography
Mélanie Roschewitz, Kenneth Styppa, Yitian Tao +10
Vision-language models (VLM) have markedly advanced AI-driven interpretation and reporting of complex medical imaging, such as computed tomography (CT). Yet, existing methods large…
CheXthought: A global multimodal dataset of clinical chain-of-thought reasoning and visual attention for chest X-ray interpretation
Sonali Sharma, Jin Long, George Shih +7
Chest X-ray interpretation is one of the most frequently performed diagnostic tasks in medicine and a primary target for AI development, yet current vision-language models are prim…
A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation
Yabin Zhang, Chong Wang, Yunhe Gao +19
Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic erro…