Fluorescence Molecular Tomography Based on Group Sparsity Priori for Morphological Reconstruction of Glioma

被引:14
作者
Jiang, Shixin [1 ,2 ,3 ]
Liu, Jie [1 ]
An, Yu [3 ]
Gao, Yuan [3 ]
Meng, Hui [3 ]
Wang, Kun [3 ]
Tian, Jie [3 ,4 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Chongqing Jiaotong Univ, Sch Informat Sci & Engn, Chongqing, Peoples R China
[3] Chinese Acad Sci, CAS Key Lab Mol Imaging, Inst Automat, Beijing 100190, Peoples R China
[4] Univ Chinese Acad Sci, Beijing 100080, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Fluorescence; Image reconstruction; Tumors; Reconstruction algorithms; Morphology; Photonics; Inverse problems; Fluorescence molecular tomography; group sparsity; image reconstruction; morphological reconstruction; ELEMENT BASED TOMOGRAPHY; THRESHOLDING ALGORITHM; OPTICAL TOMOGRAPHY; REGULARIZATION; LIGHT; MICROSCOPY; RESOLUTION; PURSUIT; SYSTEM;
D O I
10.1109/TBME.2019.2937354
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: Fluorescence molecular tomography (FMT) is an important tool for life science, which can noninvasive real-time three-dimensional (3-D) visualization for fluorescence source location. FMT is widely used in tumor research due to its high-sensitive and low cost. However, the reconstruction of FMT is difficult. Although the reconstruction methods of FMT have developed rapidly in recent years, the morphological reconstruction of FMT is still a challenge problem. Thus, the purpose of this study is to realize the morphological reconstruction performance of FMT in glioma research. Methods: In this study, group sparsity was used as a new priori information for FMT. Besides sparsity, group sparsity also takes the group structure of the fluorescent sources, which can maintain the morphological information of the sources. Fused LASSO method (FLM) was proved it can efficiently model the group sparsity prior. Thus, we utilize FLM to reconstruct the morphological information of glioma. Furthermore, to reduce the influence of the high scattering of skull, we modified the FLM for improving the accuracy of morphological reconstruction. Results: Glioma numerical simulation model and in vivo glioma model were established to evaluate the performance of morphological reconstruction of the proposed method. The results demonstrated that the proposed method was efficient to reconstruct the morphological information of glioma. Conclusion: Group sparsity priori can effectively improve the morphological accuracy of FMT reconstruction. Significance: Group sparsity can maintain the morphological information of fluorescent sources effectively, which has great application potential in FMT. The group sparsity based methods can realize the morphological reconstruction, which is of great practical significance in tumor research.
引用
收藏
页码:1429 / 1437
页数:9
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