60 citations · 262 across the 28 of their papers we have counts for
12 papers · 1 filter
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…
Large-scale Long-tailed Disease Diagnosis on Radiology Images
Qiaoyu Zheng, Weike Zhao, Chaoyi Wu +7
Developing a generalist radiology diagnosis system can greatly enhance clinical diagnostics. In this paper, we introduce RadDiag, a foundational model supporting 2D and 3D inputs a…
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.…
UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training
Jiayu Lei, Lisong Dai, Haoyun Jiang +9
Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed. How…
Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data
Chaoyi Wu, Xiaoman Zhang, Ya Zhang +2
In this study, we aim to initiate the development of Radiology Foundation Model, termed as RadFM. We consider the construction of foundational models from three perspectives, namel…
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-LLaMA: Towards Building Open-source Language Models for Medicine
Chaoyi Wu, Weixiong Lin, Xiaoman Zhang +3
Recently, Large Language Models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and quest…
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-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imaging
Chaoyi Wu, Xiaoman Zhang, Yanfeng Wang +2
In this paper, we consider the problem of disease diagnosis. Unlike the conventional learning paradigm that treats labels independently, we propose a knowledge-enhanced framework,…
Knowledge-enhanced Visual-Language Pre-training on Chest Radiology Images
Xiaoman Zhang, Chaoyi Wu, Ya Zhang +2
While multi-modal foundation models pre-trained on large-scale data have been successful in natural language understanding and vision recognition, their use in medical domains is s…
Integrating features from lymph node stations for metastatic lymph node detection
Chaoyi Wu, Feng Chang, Xiao Su +4
Metastasis on lymph nodes (LNs), the most common way of spread for primary tumor cells, is a sign of increased mortality. However, metastatic LNs are time-consuming and challenging…
MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training in Radiology
Chaoyi Wu, Xiaoman Zhang, Ya Zhang +2
In this paper, we consider enhancing medical visual-language pre-training (VLP) with domain-specific knowledge, by exploiting the paired image-text reports from the radiological da…