PIVM: Diffusion-Based Prior-Integrated Variation Modeling for Anatomically Precise Abdominal CT Synthesis

2026-03-23 · Dinglun He, Baoming Zhang, Xu Wang, Yao Hao, Deshan Yang, Ye Duan arxiv

Abdominal CT data are limited by high annotation costs and privacy constraints, which hinder the development of robust segmentation and diagnostic models. We present a Prior-Integrated Variation Modeling (PIVM) framework, a diffusion-based method for anatomically accurate CT image synthesis. Instead of generating full images from noise, PIVM predicts voxel-wise intensity variations relative to organ-specific intensity priors derived from segmentation labels. These priors and labels jointly guide the diffusion process, ensuring spatial alignment and realistic organ boundaries. Unlike latent-space diffusion models, our approach operates directly in image space while preserving the full Hounsfield Unit (HU) range, capturing fine anatomical textures without smoothing. Source code is available at https://github.com/BZNR3/PIVM.

📄 PDF Abstract BibTeX arXiv:2603.22626

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Diffusion Bridge Variational Inference for Deep Gaussian Processes

2025-09-23 · Jian Xu, Qibin Zhao, John Paisley, Delu Zeng arxiv

Deep Gaussian processes (DGPs) enable expressive hierarchical Bayesian modeling but pose substantial challenges for posterior inference, especially over inducing variables. Denoising diffusion variational inference (DDVI…

Image Reconstruction Gaussian Processes

DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior

2025-08-01 · Junzhe Lu, Jing Lin, Hongkun Dou, Ailing Zeng 외 arxiv

We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses. Building a versatile and robust full-body human pose prior remains challenging due to the inherent complexity of articulated human poses a…

Jumping VaR: Order Statistics Volatility Estimator for Jumps Classification and Market Risk Modeling

2018-03-22

This paper proposes a new integrated variance estimator based on order statistics within the framework of jump-diffusion models. Its ability to disentangle the integrated variance from the total process quadratic variati…

Time Series Time Series Analysis

VAMP-Diff: VampPrior Latent Diffusion for Photoplethysmography Modeling

2026-05-17 · Fatemeh Ghasemi Balouei, Nathan Willemsen, Mahesh Banavar, Bahman Moraffah arxiv

Photoplethysmography (PPG) has become a ubiquitous physiological signal; however, current generative models still struggle to preserve realistic waveform morphology and learn a latent structure that captures cardiac and …

Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling

2024-08-07 · Jian Xu, Zhiqi Lin, Shigui Li, Min Chen 외

Bayesian Last Layer (BLL) models focus solely on uncertainty in the output layer of neural networks, demonstrating comparable performance to more complex Bayesian models. However, the use of Gaussian priors for last laye…

Computational Efficiency Out-of-Distribution Detection Uncertainty Quantification