yqx7150/SWORD

Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-view CT Reconstruction

SWORD

Paper: Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-View CT Reconstruction

Authors: Kai Xu; Shiyu Lu; Bin Huang; Weiwen Wu; Qiegen Liu
https://ieeexplore.ieee.org/abstract/document/10403850
IEEE Transactions on Medical Imaging

Training

Wavelet-based Full-frequency Diffusion Model (WFDM)

python main_wavelet.py --config=aapm_sin_ncsnpp_wavelet.py --workdir=exp_wavelet --mode=train --eval_folder=result

Wavelet-based High-frequency Diffusion Model (WHDM)

python main_3h.py --config=aapm_sin_ncsnpp_3h.py --workdir=exp_3h --mode=train --eval_folder=result

Test

python PCsampling_demo.py

Test Data

In file './Test_CT', 12 sparse-view CT data from AAPM Challenge Data Study.

Other Related Projects

• 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]

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

• 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]

• 基于深度能量模型的低剂量CT重建
  [Paper] [Code]