Improving Multislice Electron Ptychography with a Generative Prior
Not on the map. Why?
Abstract (arXiv)
Multislice electron ptychography (MEP) is an inverse imaging technique that computationally reconstructs the highest-resolution images of atomic crystal structures from diffraction patterns. Available algorithms often solve this inverse problem iteratively but are both time consuming and produce suboptimal solutions due to their ill-posed nature. We develop MEP-Diffusion, a diffusion model trained on a large database of crystal structures specifically for MEP to augment existing iterative solvers. MEP-Diffusion is easily integrated as a generative prior into existing reconstruction methods via Diffusion Posterior Sampling (DPS). We find that this hybrid approach greatly enhances the quality of the reconstructed 3D volumes, achieving a 90.50% improvement in SSIM over existing methods.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 27 of its 57 references that are in the map. First posted on arXiv 23 Jul 2025.
Builds on
27 of 57 references.
References · 27
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2020Denoising Diffusion Implicit Modelscited by 9,781
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
- 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 3,045
- 2022Video Diffusion Modelscited by 2,305
- 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,979
- 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,430
- 2022Diffusion Posterior Sampling for General Noisy Inverse Problemscited by 1,416
- 2021Variational Diffusion Modelscited by 1,153
- 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 521
15 more
- 2022Improving Diffusion Models for Inverse Problems using Manifold Constraintscited by 508
- 2023Simple diffusion: End-to-end diffusion for high resolution imagescited by 422
- 2017Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equationscited by 373
- 2023Understanding Diffusion Objectives as the ELBO with Simple Data Augmentationcited by 304
- 2023On the Importance of Noise Scheduling for Diffusion Modelscited by 194
- 2017Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equationscited by 161
- 2023Score-Based Diffusion Models as Principled Priors for Inverse Imagingcited by 127
- 2023DiffCollage: Parallel Generation of Large Content with Diffusion Modelscited by 103
- 2024Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusioncited by 75
- 2021AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Bragg Coherent Diffraction Imagingcited by 18
- 2023Physics Constrained Unsupervised Deep Learning for Rapid, High Resolution Scanning Coherent Diffraction Reconstructioncited by 13
- 2023PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstructioncited by 9
- 2018Deep Ptych: Subsampled Fourier Ptychography using Generative Priorscited by 7
- 2022Phase Object Reconstruction for 4D-STEM using Deep Learningcited by 3
- 2025Ptychographic Image Reconstruction from Limited Data via Score-Based Diffusion Models with Physics-Guidancecited by 3
Built on by
Citing papers per year: 2025: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
- 2025Fidelity-preserving enhancement of ptychography with foundational text-to-image models
- 2026Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data
- 2023Reference-Free Isotropic 3D EM Reconstruction using Diffusion Models
- 2025Position-Blind Ptychography: Viability of image reconstruction via data-driven variational inference
- 2025DIFFRACT: Diffusion-based Restoration via Adaptive Control and Thresholding for Diffraction Imaging
- 2026Parameter Inference and Uncertainty Quantification with Diffusion Models: Extending CDI to 2D Spatial Conditioning
- 2025Generative diffusion modeling protocols for improving the Kikuchi pattern indexing in electron back-scatter diffraction
- 2024Generative Inverse Design of Crystal Structures via Diffusion Models with Transformers