3 citations · 6 across the 12 of their papers we have counts for
12 papers
RadSight: Towards Perceptually Reliable Multimodal Radiology Image Understanding
Jianqin Liu, Weiwei Cao, Wanxing Chang +7
Medical multimodal large language models (MLLMs) are increasingly expected to perform complex image understanding tasks, yet their reliability is often compromised by frequent erro…
Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy
Shaoteng Zhang, Weiwei Cao, Wanxing Chang +9
Medical images require comprehensive and accurate interpretation to support the diagnosis of diverse clincial conditions. Recent vision-language generalist models offer broad task…
AtomiMed: Hierarchical Atomic Fact-Checking for Universal Clinical-Aware Medical Report Evaluation
Yuan Wang, Wanxing Chang, Songtao Jiang +8
Traditional metrics for Medical Report Generation (MRG) predominantly rely on surface-level n-gram overlap, which fails to capture clinical factual accuracy and often overlooks cat…
Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography
Bowen Shi, Weiwei Cao, Ruifeng Yuan +5
Vision-language pre-training (VLP) holds great promise for general-purpose medical AI by leveraging radiology reports as rich textual supervision, yet existing methods struggle wit…
CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation
Ruifeng Yuan, Wanxing Chang, Weiwei Cao +4
The evaluation of generated reports remains a critical challenge in Computed Tomography (CT) report generation, due to the large volume of text, the diversity and complexity of fin…
Boosting Vision Semantic Density with Anatomy Normality Modeling for Medical Vision-language Pre-training
Weiwei Cao, Jianpeng Zhang, Zhongyi Shui +8
Vision-language pre-training (VLP) has great potential for developing multifunctional and general medical diagnostic capabilities. However, aligning medical images with a low signa…
UniReg: Conditional Unified Model for Medical Image Registration
Zi Li, Jianpeng Zhang, Tai Ma +7
Learning-based medical image registration has matched the accuracy of conventional methods while offering superior computational efficiency. However, existing approaches suffer fro…
Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding
Zhongyi Shui, Jianpeng Zhang, Weiwei Cao +8
Artificial intelligence (AI) shows great potential in assisting radiologists to improve the efficiency and accuracy of medical image interpretation and diagnosis. However, a versat…
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…
Bootstrapping Chest CT Image Understanding by Distilling Knowledge from X-ray Expert Models
Weiwei Cao, Jianpeng Zhang, Yingda Xia +7
Radiologists highly desire fully automated versatile AI for medical imaging interpretation. However, the lack of extensively annotated large-scale multi-disease datasets has hinder…
CT-GLIP: 3D Grounded Language-Image Pretraining with CT Scans and Radiology Reports for Full-Body Scenarios
Jingyang Lin, Yingda Xia, Jianpeng Zhang +5
3D medical vision-language (VL) pretraining has shown potential in radiology by leveraging large-scale multimodal datasets with CT-report pairs. However, existing methods primarily…
Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration
Tony C. W. Mok, Zi Li, Yunhao Bai +9
Establishing dense anatomical correspondence across distinct imaging modalities is a foundational yet challenging procedure for numerous medical image analysis studies and image-gu…