mlsanityData to 14 Oct 2026

Physics-Guided Diffusion Priors for Multi-Slice Reconstruction in Scientific Imaging

arXiv 2512.06977 ↗First posted 7 Dec 2025eess.IV cs.LGcited by 0

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Accurate multi-slice reconstruction from limited measurement data is crucial to speed up the acquisition process in medical and scientific imaging. However, it remains challenging due to the ill-posed nature of the problem and the high computational and memory demands. We propose a framework that addresses these challenges by integrating partitioned diffusion priors with physics-based constraints. By doing so, we substantially reduce memory usage per GPU while preserving high reconstruction quality, outperforming both physics-only and full multi-slice reconstruction baselines for different modalities, namely Magnetic Resonance Imaging (MRI) and four-dimensional Scanning Transmission Electron Microscopy (4D-STEM). Additionally, we show that the proposed method improves in-distribution accuracy as well as strong generalization to out-of-distribution datasets.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 13 of its 29 references that are in the map. First posted on arXiv 7 Dec 2025.

Builds on

13 of 29 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024MRI Reconstruction with Regularized 3D Diffusion Model (R3DM)25 Dec
  2. 2022Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models19 Nov

Other references · 11

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  4. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
  5. 2022Video Diffusion Modelscited by 2,305
  6. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,043
  7. 2018Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challengecited by 511
  8. 2018fastMRI: An Open Dataset and Benchmarks for Accelerated MRIcited by 470
  9. 2024On the Content Bias in Fr'echet Video Distancecited by 52
  10. 2024Beyond FVD: Enhanced Evaluation Metrics for Video Generation Qualitycited by 22
  11. 2018Accelerated Wirtinger Flow: A fast algorithm for ptychographycited by 5

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  4. 2024Resolution-Robust 3D MRI Reconstruction with 2D Diffusion Priors: Diverse-Resolution Training Outperforms Interpolation
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