most citedTowards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

18 citations · 57 across the 7 of their papers we have counts for

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cs.CV20245 cited

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…

cs.CV20235 cited

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…

cs.CV202318 cited

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…

cs.CV202314 cited

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…

cs.CV20237 cited

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,…

cs.CV20234 cited

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…