Research Papers: General

Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function

[+] Author Affiliations
Yu An

Beijing Jiaotong University, School of Computer and Information, Department of Biomedical Engineering, No. 3 Shangyuancun Road, Beijing 100044, China

Chinese Academy of Sciences, Institute of Automation, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Beijing, China

Jie Liu, Guanglei Zhang, Shixin Jiang

Beijing Jiaotong University, School of Computer and Information, Department of Biomedical Engineering, No. 3 Shangyuancun Road, Beijing 100044, China

Jinzuo Ye, Yamin Mao, Wenting Shang, Yang Du, Chongwei Chi

Chinese Academy of Sciences, Institute of Automation, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Beijing, China

Jie Tian

Chinese Academy of Sciences, Institute of Automation, Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Beijing, China

Chinese Academy of Sciences, Institute of Automation, Beijing Key Laboratory of Molecular Imaging, No. 95 Zhongguancun East Road, Beijing 100190, China

J. Biomed. Opt. 20(10), 105003 (Oct 09, 2015). doi:10.1117/1.JBO.20.10.105003
History: Received July 2, 2015; Accepted September 15, 2015
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Abstract.  Fluorescence molecular tomography (FMT) is a promising tool in the study of cancer, drug discovery, and disease diagnosis, enabling noninvasive and quantitative imaging of the biodistribution of fluorophores in deep tissues via image reconstruction techniques. Conventional reconstruction methods based on the finite-element method (FEM) have achieved acceptable stability and efficiency. However, some inherent shortcomings in FEM meshes, such as time consumption in mesh generation and a large discretization error, limit further biomedical application. In this paper, we propose a meshless method for reconstruction of FMT (MM-FMT) using compactly supported radial basis functions (CSRBFs). With CSRBFs, the image domain can be accurately expressed by continuous CSRBFs, avoiding the discretization error to a certain degree. After direct collocation with CSRBFs, the conventional optimization techniques, including Tikhonov, L1-norm iteration shrinkage (L1-IS), and sparsity adaptive matching pursuit, were adopted to solve the meshless reconstruction. To evaluate the performance of the proposed MM-FMT, we performed numerical heterogeneous mouse experiments and in vivo bead-implanted mouse experiments. The results suggest that the proposed MM-FMT method can reduce the position error of the reconstruction result to smaller than 0.4 mm for the double-source case, which is a significant improvement for FMT.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Yu An ; Jie Liu ; Guanglei Zhang ; Jinzuo Ye ; Yamin Mao, et al.
"Meshless reconstruction method for fluorescence molecular tomography based on compactly supported radial basis function", J. Biomed. Opt. 20(10), 105003 (Oct 09, 2015). ; http://dx.doi.org/10.1117/1.JBO.20.10.105003


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