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Cycle Diffusion Model for Counterfactual Image Generation
Fangrui Huang, Alan Wang, Binxu Li +5
Deep generative models have demonstrated remarkable success in medical image synthesis. However, ensuring conditioning faithfulness and high-quality synthetic images for direct or…
Integrating Anatomical Priors into a Causal Diffusion Model
Binxu Li, Wei Peng, Mingjie Li +2
3D brain MRI studies often examine subtle morphometric differences between cohorts that are hard to detect visually. Given the high cost of MRI acquisition, these studies could gre…
WASABI: A Metric for Evaluating Morphometric Plausibility of Synthetic Brain MRIs
Bahram Jafrasteh, Wei Peng, Cheng Wan +3
Generative models enhance neuroimaging through data augmentation, quality improvement, and rare condition studies. Despite advances in realistic synthetic MRIs, evaluations focus o…
Vision Language Models in Medicine
Beria Chingnabe Kalpelbe, Angel Gabriel Adaambiik, Wei Peng
With the advent of Vision-Language Models (VLMs), medical artificial intelligence (AI) has experienced significant technological progress and paradigm shifts. This survey provides…
Diffusion Models for Computational Neuroimaging: A Survey
Haokai Zhao, Haowei Lou, Lina Yao +4
Computational neuroimaging involves analyzing brain images or signals to provide mechanistic insights and predictive tools for human cognition and behavior. While diffusion models…