English

Block Matching Frame based Material Reconstruction for Spectral CT

Computer Vision and Pattern Recognition 2020-01-08 v2

Abstract

Spectral computed tomography (CT) has a great potential in material identification and decomposition. To achieve high-quality material composition images and further suppress the x-ray beam hardening artifacts, we first propose a one-step material reconstruction model based on Taylor first-order expansion. Then, we develop a basic material reconstruction method named material simultaneous algebraic reconstruction technique (MSART). Considering the local similarity of each material image, we incorporate a powerful block matching frame (BMF) into the material reconstruction (MR) model and generate a BMF based MR (BMFMR) method. Because the BMFMR model contains the L0-norm problem, we adopt a split-Bregman method for optimization. The numerical simulation and physical phantom experiment results validate the correctness of the material reconstruction algorithms and demonstrate that the BMF regularization outperforms the total variation and no-local mean regularizations.

Keywords

Cite

@article{arxiv.1810.10346,
  title  = {Block Matching Frame based Material Reconstruction for Spectral CT},
  author = {Weiwen Wu and Qian Wang and Fenglin Liu and Yining Zhu and Hengyong Yu},
  journal= {arXiv preprint arXiv:1810.10346},
  year   = {2020}
}

Comments

More details can refer to https://iopscience.iop.org/article/10.1088/1361-6560/ab51db/pdf

R2 v1 2026-06-23T04:51:11.920Z