6 papers
Interpretable Multimodal Cancer Prototyping with Whole Slide Images and Incompletely Paired Genomics
Yupei Zhang, Yating Huang, Wanming Hu +3
Multimodal approaches that integrate histology and genomics hold strong potential for precision oncology. However, phenotypic and genotypic heterogeneity limits the quality of intr…
Citrus-V: Advancing Medical Foundation Models with Unified Medical Image Grounding for Clinical Reasoning
Guoxin Wang, Jun Zhao, Xinyi Liu +8
Medical imaging provides critical evidence for clinical diagnosis, treatment planning, and surgical decisions, yet most existing imaging models are narrowly focused and require mul…
Reframing SAR Target Recognition as Visual Reasoning: A Chain-of-Thought Dataset with Multimodal LLMs
Chaoran Li, Xingguo Xu, Siyuan Mu
In the context of Synthetic Aperture Radar (SAR) image recognition, traditional methods often struggle with the intrinsic limitations of SAR data, such as weak texture, high noise,…
Phy-Diff: Physics-guided Hourglass Diffusion Model for Diffusion MRI Synthesis
Juanhua Zhang, Ruodan Yan, Alessandro Perelli +2
Diffusion MRI (dMRI) is an important neuroimaging technique with high acquisition costs. Deep learning approaches have been used to enhance dMRI and predict diffusion biomarkers th…
Genomics-guided Representation Learning for Pathologic Pan-cancer Tumor Microenvironment Subtype Prediction
Fangliangzi Meng, Hongrun Zhang, Ruodan Yan +3
The characterization of Tumor MicroEnvironment (TME) is challenging due to its complexity and heterogeneity. Relatively consistent TME characteristics embedded within highly specif…
Spatiotemporal Graph Neural Network Modelling Perfusion MRI
Ruodan Yan, Carola-Bibiane Schönlieb, Chao Li
Perfusion MRI (pMRI) offers valuable insights into tumor vascularity and promises to predict tumor genotypes, thus benefiting prognosis for glioma patients, yet effective models ta…