Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction

Chi Ding, Qingchao Zhang, Ge Wang, Xiaojing Ye, Yunmei Chen
6/5/2023
cs.CV

No official code found. Best implementation: chrisdcs/LAMA-Learned-Alternating-Minimization-Algorithm (15 stars, last commit 2023-11-27).

Abstract

We propose a novel Learned Alternating Minimization Algorithm (LAMA) for dual-domain sparse-view CT image reconstruction. LAMA is naturally induced by a variational model for CT reconstruction with learnable nonsmooth nonconvex regularizers, which are parameterized as composite functions of deep networks in both image and sinogram domains. To minimize the objective of the model, we incorporate the smoothing technique and residual learning architecture into the design of LAMA. We show that LAMA substantially reduces network complexity, improves memory efficiency and reconstruction accuracy, and is provably convergent for reliable reconstructions. Extensive numerical experiments demonstrate that LAMA outperforms existing methods by a wide margin on multiple benchmark CT datasets.

View on arXivView PDF

Code Implementations(1)

chrisdcs/LAMA-Learned-Alternating-Minimization-AlgorithmCommunity100%
153Python, Jupyter NotebookJul 21, 20222 years ago

Similar Papers

LAMA: Stable Dual-Domain Deep Reconstruction For Sparse-View CT

86% match2024

WNet: A data-driven dual-domain denoising model for sparse-view computed tomography with a trainable reconstruction layer

83% match2022

DULDA: Dual-domain Unsupervised Learned Descent Algorithm for PET image reconstruction

83% match2023

Physics-Guided Null-Space Diffusion with Sparse Masking for Corrective Sparse-View CT Reconstruction

83% match2025

Rethinking Dual-Domain Undersampled MRI reconstruction: domain-specific design from the perspective of the receptive field

83% match2023

MVMS-RCN: A Dual-Domain Unfolding CT Reconstruction with Multi-sparse-view and Multi-scale Refinement-correction

83% match1 repo32024

Cite this paper

@article{ding2023learned,
  title  = {Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction},
  author = {Chi Ding and Qingchao Zhang and Ge Wang and Xiaojing Ye and Yunmei Chen},
  year   = {2023},
  eprint = {2306.02644},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.02644v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2306.02644.svg)](https://codeofpaper.com/paper/2306.02644)

Discussion