Research Papers: General

Fluorescence molecular tomography reconstruction via discrete cosine transform-based regularization

[+] Author Affiliations
Junwei Shi, Jiulou Zhang, Jing Bai

Tsinghua University, Department of Biomedical Engineering, School of Medicine, Haidian District, Beijing 100084, China

Fei Liu

Tsinghua University, Department of Biomedical Engineering, School of Medicine, Haidian District, Beijing 100084, China

Tsinghua University, Tsinghua-Peking Center for Life Sciences, School of Medicine, Haidian District, Beijing 100084, China

Jianwen Luo

Tsinghua University, Department of Biomedical Engineering, School of Medicine, Haidian District, Beijing 100084, China

Tsinghua University, Center for Biomedical Imaging Research, School of Medicine, Haidian District, Beijing 100084, China

J. Biomed. Opt. 20(5), 055004 (May 13, 2015). doi:10.1117/1.JBO.20.5.055004
History: Received February 7, 2015; Accepted April 15, 2015
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Abstract.  Fluorescence molecular tomography (FMT) as a noninvasive imaging modality has been widely used for biomedical preclinical applications. However, FMT reconstruction suffers from severe ill-posedness, especially when a limited number of projections are used. In order to improve the quality of FMT reconstruction results, a discrete cosine transform (DCT) based reweighted L1-norm regularization algorithm is proposed. In each iteration of the reconstruction process, different reweighted regularization parameters are adaptively assigned according to the values of DCT coefficients to suppress the reconstruction noise. In addition, the permission region of the reconstructed fluorophores is adaptively constructed to increase the convergence speed. In order to evaluate the performance of the proposed algorithm, physical phantom and in vivo mouse experiments with a limited number of projections are carried out. For comparison, different L1-norm regularization strategies are employed. By quantifying the signal-to-noise ratio (SNR) of the reconstruction results in the phantom and in vivo mouse experiments with four projections, the proposed DCT-based reweighted L1-norm regularization shows higher SNR than other L1-norm regularizations employed in this work.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Junwei Shi ; Fei Liu ; Jiulou Zhang ; Jianwen Luo and Jing Bai
"Fluorescence molecular tomography reconstruction via discrete cosine transform-based regularization", J. Biomed. Opt. 20(5), 055004 (May 13, 2015). ; http://dx.doi.org/10.1117/1.JBO.20.5.055004


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