Adaptive regularized method based on homotopy for sparse fluorescence tomography

Determining an appropriate regularization parameter is often challenging work because it has a narrow range and varies with problems, which is likely to lead to large reconstruction errors. In this contribution, an adaptive regularized method based on homotopy is presented for sparse fluorescence to...

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Bibliographic Details
Published in:Applied optics (2004) 2013-04, Vol.52 (11), p.2374-2384
Main Authors: Xue, Zhenwen, Ma, Xibo, Zhang, Qian, Wu, Ping, Yang, Xin, Tian, Jie
Format: Article
Language:English
Subjects:
Algorithms
Fluorescence
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Microscopy, Fluorescence - methods
Reproducibility of Results
Sensitivity and Specificity
Tomography, Optical - methods
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Summary:Determining an appropriate regularization parameter is often challenging work because it has a narrow range and varies with problems, which is likely to lead to large reconstruction errors. In this contribution, an adaptive regularized method based on homotopy is presented for sparse fluorescence tomography reconstruction. Due to the adaptive regularization strategy, the proposed method is always able to reconstruct sources accurately independent of the estimation of the regularization parameter. Moreover, the proposed method is about two orders of magnitude faster than the two contrasting methods. Numerical and in vivo mouse experiments have been employed to validate the robustness and efficiency of the proposed method.
ISSN:1559-128X
2155-3165
DOI:10.1364/ao.52.002374