Literature DB >> 31947271

Inner Focus Iterative Reconstruction Method with the Interlaced Phase Stepping Scanning for Grating-based Phase Contrast Tomography.

Zhishang Hou, Jun Zhao, Jianqi Sun.   

Abstract

The potential clinical application of grating-based phase contrast computed tomography (GPCCT) requires moderate scanning time to reduce the radiation dose, which are not met by traditional GPCCT phase stepping (PS) method. Previous studies have proposed the interlaced scanning method to reduce the scanning time. However, due to the projection number demanded by the analysis reconstruction algorithm, the projection and scanning time cannot be further reduced. In this paper, we proposed an iterative algorithm based on the interlaced PS scanning for GPCCT, which was capable in reducing the motion artifacts during reconstruction as the same as the inner focus (IF) method we raised before. Furthermore, the iterative procedure is expected to introduce some machine learning method and allows a lower radiation dose while maintaining the image quality. Our proposed method mainly consists of three steps: 1) Interlaced data acquisition, 2) Phase retrieval, 3) Inner focus iterative reconstruction. Through changing the virtual rotation center and merging high resolution regions, images without severe boundary blurring can be reconstructed with fast scan speed. The experiment result indicates that our method can reconstruct GPCCT data with interlaced PS scanning.

Mesh:

Year:  2019        PMID: 31947271     DOI: 10.1109/EMBC.2019.8857845

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Computed Tomography Three-Dimensional Reconstruction Algorithm in the Diagnosis of Periodontitis and Its Correlation with Hypertension.

Authors:  Lingling Xu; Jiaxin Pan; Jue Liu; Zhong Guan; Lu Zhao
Journal:  Comput Math Methods Med       Date:  2022-07-01       Impact factor: 2.809

2.  Effect of Interventional Therapy on Iliac Venous Compression Syndrome Evaluated and Diagnosed by Artificial Intelligence Algorithm-Based Ultrasound Images.

Authors:  Ye Bai; Fei Bo; Wencan Ma; Hongwei Xu; Dawei Liu
Journal:  J Healthc Eng       Date:  2021-07-22       Impact factor: 2.682

  2 in total

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