60 citations · 144 across the 12 of their papers we have counts for
12 papers
A Vision-language Framework for Comparative Reasoning in Radiology
Tengfei Zhang, Ziheng Zhao, Xiaoman Zhang +5
Medical imaging artificial intelligence has achieved strong performance in isolated image interpretation, but remains poorly aligned with radiological practice, where diagnosis and…
Rethinking Whole-Body CT Image Interpretation: An Abnormality-Centric Approach
Ziheng Zhao, Lisong Dai, Ya Zhang +2
Automated interpretation of CT images-particularly localizing and describing abnormal findings across multi-plane and whole-body scans-remains a significant challenge in clinical r…
RadIR: A Scalable Framework for Multi-Grained Medical Image Retrieval via Radiology Report Mining
Tengfei Zhang, Ziheng Zhao, Chaoyi Wu +4
Developing advanced medical imaging retrieval systems is challenging due to the varying definitions of `similar images' across different medical contexts. This challenge is compoun…
M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging
Jinghao Feng, Qiaoyu Zheng, Chaoyi Wu +4
Agentic AI systems have gained significant attention for their ability to autonomously perform complex tasks. However, their reliance on well-prepared tools limits their applicabil…
MRGen: Segmentation Data Engine for Underrepresented MRI Modalities
Haoning Wu, Ziheng Zhao, Ya Zhang +2
Training medical image segmentation models for rare yet clinically important imaging modalities is challenging due to the scarcity of annotated data, and manual mask annotations ca…
LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation Models
Haolin Li, Yuhang Zhou, Ziheng Zhao +5
The widespread adoption of large-scale pre-training techniques has significantly advanced the development of medical foundation models, enabling them to serve as versatile tools ac…
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT Analysis
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Developing generalist foundation model has recently attracted tremendous attention among researchers in the field of AI for Medicine (AI4Medicine). A pivotal insight in developing…
Large-Vocabulary Segmentation for Medical Images with Text Prompts
Ziheng Zhao, Yao Zhang, Chaoyi Wu +5
This paper aims to build a model that can Segment Anything in 3D medical images, driven by medical terminologies as Text prompts, termed as SAT. Our main contributions are three-fo…
Can GPT-4V(ision) Serve Medical Applications? Case Studies on GPT-4V for Multimodal Medical Diagnosis
Chaoyi Wu, Jiayu Lei, Qiaoyu Zheng +8
Driven by the large foundation models, the development of artificial intelligence has witnessed tremendous progress lately, leading to a surge of general interest from the public.…
PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao +4
Medical Visual Question Answering (MedVQA) presents a significant opportunity to enhance diagnostic accuracy and healthcare delivery by leveraging artificial intelligence to interp…
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents
Weixiong Lin, Ziheng Zhao, Xiaoman Zhang +4
Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due to data scarcity. To address t…
K-Space Transformer for Undersampled MRI Reconstruction
Ziheng Zhao, Tianjiao Zhang, Weidi Xie +2
This paper considers the problem of undersampled MRI reconstruction. We propose a novel Transformer-based framework for directly processing signal in k-space, going beyond the limi…