5 citations · 26 across the 9 of their papers we have counts for
9 papers
MRScore: Evaluating Radiology Report Generation with LLM-based Reward System
Yunyi Liu, Zhanyu Wang, Yingshu Li +4
In recent years, automated radiology report generation has experienced significant growth. This paper introduces MRScore, an automatic evaluation metric tailored for radiology repo…
MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generation
Ling Yang, Zhanyu Wang, Zhenghao Chen +2
Multimodal Large Language Models (MLLMs) have shown success in various general image processing tasks, yet their application in medical imaging is nascent, lacking tailored models.…
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis
Yingshu Li, Yunyi Liu, Zhanyu Wang +7
This work conducts an evaluation of GPT-4V's multimodal capability for medical image analysis, with a focus on three representative tasks of radiology report generation, medical vi…
R2GenGPT: Radiology Report Generation with Frozen LLMs
Zhanyu Wang, Lingqiao Liu, Lei Wang +1
Large Language Models (LLMs) have consistently showcased remarkable generalization capabilities when applied to various language tasks. Nonetheless, harnessing the full potential o…
METransformer: Radiology Report Generation by Transformer with Multiple Learnable Expert Tokens
Zhanyu Wang, Lingqiao Liu, Lei Wang +1
In clinical scenarios, multi-specialist consultation could significantly benefit the diagnosis, especially for intricate cases. This inspires us to explore a "multi-expert joint di…
Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder
Yunyi Liu, Zhanyu Wang, Dong Xu +1
Medical Visual Question Answering (VQA) systems play a supporting role to understand clinic-relevant information carried by medical images. The questions to a medical image include…
A Medical Semantic-Assisted Transformer for Radiographic Report Generation
Zhanyu Wang, Mingkang Tang, Lei Wang +2
Automated radiographic report generation is a challenging cross-domain task that aims to automatically generate accurate and semantic-coherence reports to describe medical images.…
CLIP4Caption ++: Multi-CLIP for Video Caption
Mingkang Tang, Zhanyu Wang, Zhaoyang Zeng +2
This report describes our solution to the VALUE Challenge 2021 in the captioning task. Our solution, named CLIP4Caption++, is built on X-Linear/X-Transformer, which is an advanced…
CLIP4Caption: CLIP for Video Caption
Mingkang Tang, Zhanyu Wang, Zhenhua Liu +3
Video captioning is a challenging task since it requires generating sentences describing various diverse and complex videos. Existing video captioning models lack adequate visual r…