Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusion

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

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

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

• REDAEP: Robust and Enhanced Denoising Autoencoding Prior for Sparse-View CT Reconstruction
  [Paper] [Code] [PPT]

• Wavelet-improved score-based generative model for medical imaging
  [Paper]

• 基于深度能量模型的低剂量CT重建
  [Paper] [Code]

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

• Dual-Domain Collaborative Diffusion Sampling for Multi-Source Stationary Computed Tomography Reconstruction
  [Paper] [Code]

• Low-rank Angular Prior Guided Multi-diffusion Model for Few-shot Low-dose CT Reconstruction
  [Paper] [Code]

• Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusion
  [Paper] [Code]

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

• Ordered-subsets Multi-diffusion Model for Sparse-view CT Reconstruction
  [Paper]

• Virtual-mask Informed Prior for Sparse-view Dual-Energy CT Reconstruction
  [Paper] [Code]

• Raw_data_generation [Code]

• PRO: Projection Domain Synthesis for CT Imaging [Paper] [Code]

• UniSino: Physics-Driven Foundational Model for Universal CT Sinogram Standardization[Paper] [Code]

• Diffusion Models for Medical Imaging [Paper] [Code] [PPT]