10 papers
X-WIN: Building Chest Radiograph World Model via Predictive Sensing
Zefan Yang, Ge Wang, James Hendler +2
Chest X-ray radiography (CXR) is an essential medical imaging technique for disease diagnosis. However, as 2D projectional images, CXRs are limited by structural superposition and…
A Deep Learning System for Rapid and Accurate Warning of Acute Aortic Syndrome on Non-contrast CT in China
Yujian Hu, Yilang Xiang, Yan-Jie Zhou +41
The accurate and timely diagnosis of acute aortic syndromes (AAS) in patients presenting with acute chest pain remains a clinical challenge. Aortic CT angiography (CTA) is the imag…
Development and Validation of a Large Language Model for Generating Fully-Structured Radiology Reports
Chuang Niu, Md Sayed Tanveer, Md Zabirul Islam +5
Current LLMs for creating fully-structured reports face the challenges of formatting errors, content hallucinations, and privacy leakage issues when uploading data to external serv…
Chest X-ray Foundation Model with Global and Local Representations Integration
Zefan Yang, Xuanang Xu, Jiajin Zhang +3
Chest X-ray (CXR) is the most frequently ordered imaging test, supporting diverse clinical tasks from thoracic disease detection to postoperative monitoring. However, task-specific…
Xray2Xray: World Model from Chest X-rays with Volumetric Context
Zefan Yang, Xinrui Song, Xuanang Xu +4
Chest X-rays (CXRs) are the most widely used medical imaging modality and play a pivotal role in diagnosing diseases. However, as 2D projection images, CXRs are limited by structur…
Evaluating Automated Radiology Report Quality through Fine-Grained Phrasal Grounding of Clinical Findings
Razi Mahmood, Pingkun Yan, Diego Machado Reyes +5
Several evaluation metrics have been developed recently to automatically assess the quality of generative AI reports for chest radiographs based only on textual information using l…