5 papers
ColoDiff: Integrating Dynamic Consistency With Content Awareness for Colonoscopy Video Generation
Junhu Fu, Shuyu Liang, Wutong Li +9
Colonoscopy video generation delivers dynamic, information-rich data critical for diagnosing intestinal diseases, particularly in data-scarce scenarios. High-quality video generati…
Can We Infer Confidential Properties of Training Data from LLMs?
Pengrun Huang, Chhavi Yadav, Kamalika Chaudhuri +1
Large language models (LLMs) are increasingly fine-tuned on domain-specific datasets to support applications in fields such as healthcare, finance, and law. These fine-tuning datas…
VAP-Diffusion: Enriching Descriptions with MLLMs for Enhanced Medical Image Generation
Peng Huang, Junhu Fu, Bowen Guo +3
As the appearance of medical images is influenced by multiple underlying factors, generative models require rich attribute information beyond labels to produce realistic and divers…
Diff-CXR: Report-to-CXR generation through a disease-knowledge enhanced diffusion model
Peng Huang, Bowen Guo, Shuyu Liang +3
Text-To-Image (TTI) generation is significant for controlled and diverse image generation with broad potential applications. Although current medical TTI methods have made some pro…
Chest-Diffusion: A Light-Weight Text-to-Image Model for Report-to-CXR Generation
Peng Huang, Xue Gao, Lihong Huang +4
Text-to-image generation has important implications for generation of diverse and controllable images. Several attempts have been made to adapt Stable Diffusion (SD) to the medical…