12 papers
Foundation VAEs for 3D CT Reconstruction, Augmentation, and Generation
Qi Chen, Shuhan Ding, Yu Gu +5
Variational autoencoders (VAEs) compress high resolution CT volumes into compact latents while preserving clinically relevant structure. However, training CT-specific VAEs from scr…
CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalization
Linkai Peng, Cuiling Sun, Zheyuan Zhang +10
Automatic pancreas segmentation is fundamental to abdominal MRI analysis, yet deep learning models trained on one MRI sequence often fail catastrophically when applied to another-a…
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Meissa: Multi-modal Medical Agentic Intelligence
Yixiong Chen, Xinyi Bai, Yue Pan +2
Multi-modal large language models (MM-LLMs) have shown strong performance in medical image understanding and clinical reasoning. Recent medical agent systems extend them with tool…
Expectation-Maximization as the Engine of Scalable Medical Intelligence
Wenxuan Li, Pedro R. A. S. Bassi, Tianyu Lin +19
Large, high-quality, annotated datasets are the foundation of medical AI research, but constructing even a small, moderate-quality, annotated dataset can take years of effort from…
RadGPT: Constructing 3D Image-Text Tumor Datasets
Pedro R. A. S. Bassi, Mehmet Can Yavuz, Kang Wang +7
Cancers identified in CT scans are usually accompanied by detailed radiology reports, but publicly available CT datasets often lack these essential reports. This absence limits the…