4 papers
CONFLUX: A Latent Diffusion Model for 3D Chest-CT Synthesis with RL Post-Training
Max Van Puyvelde, Halil Ibrahim Gulluk, Wim Van Criekinge +1
Controllable generative models of 3D medical images can synthesize volumes with specified clinical attributes, but this demands samples that are simultaneously high-fidelity, nativ…
BrainG3N: A Dual-Purpose Tokenizer for Controllable 3D Brain MRI Generation
Max Van Puyvelde, Ibrahim Gulluk, Wim Van Criekinge +1
Three-dimensional (3D) brain MRI is central to clinical neurology and neuro-oncology, where generative models could augment under-represented cohorts, simulate disease trajectories…
SAGE-FM: A lightweight and interpretable spatial transcriptomics foundation model
Xianghao Zhan, Jingyu Xu, Yuanning Zheng +2
Spatial transcriptomics enables spatial gene expression profiling, motivating computational models that capture spatially conditioned regulatory relationships. We introduce SAGE-FM…
Benchmarking Chest X-ray Diagnosis Models Across Multinational Datasets
Qinmei Xu, Yiheng Li, Xianghao Zhan +10
Foundation models leveraging vision-language pretraining have shown promise in chest X-ray (CXR) interpretation, yet their real-world performance across diverse populations and dia…