yqx7150/Diffusion-Models-for-Medical-Imaging

Diffusion Models for Medical Imaging

Diffusion-Models-for-Medical-Imaging

Diffusion Models for Medical Imaging

Learning from DAE to DSM

• Highly Undersampled Magnetic Resonance Imaging Reconstruction using Autoencoding Priors
  [Paper] [Code] [Slide] [数学图像联盟会议交流PPT]

• High-dimensional Embedding Network Derived Prior for Compressive Sensing MRI Reconstruction
  [Paper] [Code]

• Denoising Auto-encoding Priors in Undecimated Wavelet Domain for MR Image Reconstruction
  [Paper] [Paper] [Code]

• REDAEP: Robust and Enhanced Denoising Autoencoding Prior for Sparse-View CT Reconstruction
  [Paper] [Code] [PPT] [数学图像联盟会议交流PPT]

• Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors
  [Paper] [Code]

• Iterative Reconstruction for Low-Dose CT using Deep Gradient Priors of Generative Model
  [Paper] [Code] [PPT]

• Wavelet-improved Score-based Generative Model for Medical Imaging
  [Paper]

• 基于分数匹配生成模型的无透镜成像方法
  [Paper] [Code] [CIIS 2023-PPT]

• Imaging through scattering media via generative diffusion model
  [Paper] [Code]

Learning from Image Domain to Projection Domain

• Homotopic Gradients of Generative Density Priors for MR Image Reconstruction
  [Paper] [Code] [Slide]

• Universal Generative Modeling for Calibration-free Parallel MR Imaging
  [Paper] [Code] [Poster]

• WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstruction
  [Paper] [Code] [ISMRM_2022_slideliu6] [ISMRM_2022_liu]

• Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstruction
  [Paper] [Code]

• Universal Generative Modeling in Dual-domain for Dynamic MR Imaging
  [Paper] [Code]

• Physics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation
  [Paper]

• Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction
  [Paper] [Code]

• Multi-phase FZA lensless imaging via diffusion model
  [Paper] [Code] [CIIS 2023-PPT]

• Generative model for sparse photoacoustic tomography artifact removal
  [Paper]

• Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration
  [Paper] [Code]

• High-resolution iterative reconstruction at extremely low sampling rate for Fourier single-pixel imaging via diffusion model
  [Paper] [Code]

• Accelerated model-based iterative reconstruction strategy for sparse-view photoacoustic tomography aided by multi-channel autoencoder priors
  [Paper] [Code]

Learning from Large to Small Dataset

• One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstruction
  [Paper] [Code] [PPT]

• One Sample Diffusion Model in Projection Domain for Low-Dose CT Imaging
  [Paper] [Code]

• Generative Modeling in Structural-Hankel Domain for Color Image Inpainting
  [Paper] [Code] [CIIS 2023-PPT]

Learning from One to Multiple Models

• Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-view CT Reconstruction
  [Paper] [Code]

• Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction
  [Paper] [Code]

• DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Models
  [Paper] [Code]

• Diffusion Model based on Generalized Map for Accelerated MRI
  [Paper] [Code]

• MSDiff: Multi-Scale Diffusion Model for Ultra-Sparse View CT Reconstruction
  [Paper] [Code]

• Partitioned Hankel-based Diffusion Models for Few-shot Low-dose CT Reconstruction
  [Paper] [Code]

• Knowledge-driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un-supervised learning
  [Paper]

• Deep learning for fast MR imaging: a review for learning reconstruction from incomplete k-space data
  [Paper]