Laplacian manifold regularization method for fluorescence molecular tomography

Xuelei He; Xiaodong Wang; Huangjian Yi; Yanrong Chen; Xu Zhang; Jingjing Yu; Xiaowei He

doi:10.1117/1.JBO.22.4.045009

21 April 2017 Laplacian manifold regularization method for fluorescence molecular tomography

Xuelei He, Xiaodong Wang, Huangjian Yi, Yanrong Chen, Xu Zhang, Jingjing Yu, Xiaowei He

Author Affiliations +

Journal of Biomedical Optics, Vol. 22, Issue 4, 045009 (April 2017). https://doi.org/10.1117/1.JBO.22.4.045009

Abstract

Sparse regularization methods have been widely used in fluorescence molecular tomography (FMT) for stable three-dimensional reconstruction. Generally, ℓ1-regularization-based methods allow for utilizing the sparsity nature of the target distribution. However, in addition to sparsity, the spatial structure information should be exploited as well. A joint ℓ1 and Laplacian manifold regularization model is proposed to improve the reconstruction performance, and two algorithms (with and without Barzilai–Borwein strategy) are presented to solve the regularization model. Numerical studies and in vivo experiment demonstrate that the proposed Gradient projection-resolved Laplacian manifold regularization method for the joint model performed better than the comparative algorithm for ℓ1 minimization method in both spatial aggregation and location accuracy.

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Xuelei He, Xiaodong Wang, Huangjian Yi, Yanrong Chen, Xu Zhang, Jingjing Yu, and Xiaowei He "Laplacian manifold regularization method for fluorescence molecular tomography," Journal of Biomedical Optics 22(4), 045009 (21 April 2017). https://doi.org/10.1117/1.JBO.22.4.045009

Received: 7 December 2016; Accepted: 7 April 2017; Published: 21 April 2017

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