CASIA OpenIR  > 中国科学院分子影像重点实验室
Morphological Reconstruction of Fluorescence Molecular Tomography Based on Nonlocal Total Variation Regularization for Tracer Distribution in Glioma
Hui Meng1,2; Yuan Gao1,2; Kun Wang1,2,3; Jie Tian1,3,4
2019
Conference NameSPIE BiOS 2019
Conference Date2019.2.1-2019.2.6
Conference PlaceSan Francisco, USA
Abstract

The high sensitivity and low cost of fluorescence imaging enables fluorescence molecular tomography (FMT) as a powerful noninvasive technique in applications of tracer distribution visualization. With the development of targeted fluorescence tracer, FMT has been widely used to localize the tumor. However, the visualization of probe distribution in
tumor and surrounding region is still a challenge for FMT reconstruction. In this study, we proposed a novel nonlocal total variation (NLTV) regularization method, which is based on structure prior information. To build the NLTV regularization term, we consider the first order difference between the voxel and its four nearest neighbors. Furthermore, we assume that the variance of fluorescence intensity between any two voxels has a non-linear inverse correlation with their Gaussian distance. We adopted the Gaussian distance between two voxels as the weight of the first order difference. Meanwhile, the split Bregman method was applied to minimize the optimization problem. To evaluate the robustness and feasibility of our proposed method, we designed numerical simulation experiments and in vivo experiments of xenograft orthotopic glioma models. The ex vivo fluorescent images of cryoslicing specimens were regarded as gold standard of probe distribution in biological tissue. The results demonstrated that the proposed method could recover the morphology of the tracer distribution more accurately compared with fast iterated shrinkage (FIS) method, Split Bregman-resolved TV (SBRTV) regularization method and Gaussian weighted Laplace prior (GWLP) regularization method. These results demonstrate the potential of our method for in vivo visualization of tracer distribution in xenograft orthotopic glioma models.
 

KeywordFluorescence Molecular Tomography Nonlocal Total Variation Morphological Reconstruction
DOI10.1117/12.2507622
Indexed ByEI
Language英语
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Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/38533
Collection中国科学院分子影像重点实验室
Corresponding AuthorKun Wang; Jie Tian
Affiliation1.CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China
2.the University of Chinese Academy of Sciences, Beijing, 100049, China
3.Beijing Key Laboratory of Molecular Imaging, Beijing, 1000190, China
4.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, 100191, China
Recommended Citation
GB/T 7714
Hui Meng,Yuan Gao,Kun Wang,et al. Morphological Reconstruction of Fluorescence Molecular Tomography Based on Nonlocal Total Variation Regularization for Tracer Distribution in Glioma[C],2019.
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