Literature DB >> 27845916

Evaluation of hybrid SART  +  OS  +  TV iterative reconstruction algorithm for optical-CT gel dosimeter imaging.

Yi Du1, Xiangang Wang, Xincheng Xiang, Zhouping Wei.   

Abstract

Optical computed tomography (optical-CT) is a high-resolution, fast, and easily accessible readout modality for gel dosimeters. This paper evaluates a hybrid iterative image reconstruction algorithm for optical-CT gel dosimeter imaging, namely, the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization. The mathematical theory and implementation workflow of the algorithm are detailed. Experiments on two different optical-CT scanners were performed for cross-platform validation. For algorithm evaluation, the iterative convergence is first shown, and peak-to-noise-ratio (PNR) and contrast-to-noise ratio (CNR) results are given with the cone-beam filtered backprojection (FDK) algorithm and the FDK results followed by median filtering (mFDK) as reference. The effect on spatial gradients and reconstruction artefacts is also investigated. The PNR curve illustrates that the results of SART  +  OS  +  TV finally converges to that of FDK but with less noise, which implies that the dose-OD calibration method for FDK is also applicable to the proposed algorithm. The CNR in selected regions-of-interest (ROIs) of SART  +  OS  +  TV results is almost double that of FDK and 50% higher than that of mFDK. The artefacts in SART  +  OS  +  TV results are still visible, but have been much suppressed with little spatial gradient loss. Based on the assessment, we can conclude that this hybrid SART  +  OS  +  TV algorithm outperforms both FDK and mFDK in denoising, preserving spatial dose gradients and reducing artefacts, and its effectiveness and efficiency are platform independent.

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Year:  2016        PMID: 27845916     DOI: 10.1088/0031-9155/61/24/8425

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

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Authors:  Xueli Chen; Shouping Zhu; Huiyuan Wang; Cuiping Bao; Defu Yang; Chi Zhang; Peng Lin; Ji-Xin Cheng; Yonghua Zhan; Jimin Liang; Jie Tian
Journal:  IEEE Trans Biomed Eng       Date:  2019-08-14       Impact factor: 4.538

2.  Two-stage deep learning network-based few-view image reconstruction for parallel-beam projection tomography.

Authors:  Huiyuan Wang; Nan Wang; Hui Xie; Lin Wang; Wangting Zhou; Defu Yang; Xu Cao; Shouping Zhu; Jimin Liang; Xueli Chen
Journal:  Quant Imaging Med Surg       Date:  2022-04

3.  GPU accelerated voxel-driven forward projection for iterative reconstruction of cone-beam CT.

Authors:  Yi Du; Gongyi Yu; Xincheng Xiang; Xiangang Wang
Journal:  Biomed Eng Online       Date:  2017-01-05       Impact factor: 2.819

4.  Development of a denoising convolutional neural network-based algorithm for metal artifact reduction in digital tomosynthesis for arthroplasty: A phantom study.

Authors:  Tsutomu Gomi; Rina Sakai; Hidetake Hara; Yusuke Watanabe; Shinya Mizukami
Journal:  PLoS One       Date:  2019-09-13       Impact factor: 3.240

5.  Improved digital chest tomosynthesis image quality by use of a projection-based dual-energy virtual monochromatic convolutional neural network with super resolution.

Authors:  Tsutomu Gomi; Hidetake Hara; Yusuke Watanabe; Shinya Mizukami
Journal:  PLoS One       Date:  2020-12-31       Impact factor: 3.240

6.  Three-Dimensional Dosimetry by Optical-CT and Radiochromic Gel Dosimeter of a Multiple Isocenter Craniospinal Radiation Therapy Procedure.

Authors:  Matheus Antonio da Silveira; Juliana Fernandes Pavoni; Alexandre Colello Bruno; Gustavo Viani Arruda; Oswaldo Baffa
Journal:  Gels       Date:  2022-09-13

7.  Use of a Total Variation Minimization Iterative Reconstruction Algorithm to Evaluate Reduced Projections during Digital Breast Tomosynthesis.

Authors:  Tsutomu Gomi; Yukio Koibuchi
Journal:  Biomed Res Int       Date:  2018-06-19       Impact factor: 3.411

  7 in total

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