Purpose

Fluorescence molecular tomography (FMT) is a promising technique for three-dimensional (3D) visualization of biomarkers in small animals. Morphological reconstruction is valuable and necessary for further applications of FMT owing to its innate requirement for knowledge of the molecular probe distributions.

Procedures

In this study, a Laplacian manifold regularization joint ℓ_1/2-norm model is proposed for morphological reconstruction and solved by a nonconvex algorithm commonly referred to as the half-threshold algorithm. The model is combined with the structural and sparsity priors to achieve the location and structure of the target. In addition, two improvement forms (truncated and hybrid truncated forms) are proposed for better morphological reconstruction. The truncated form is proposed for balancing the sharpness and smoothness of the boundary of reconstruction. A hybrid truncated form is proposed for more structural priors. To evaluate the proposed methods, three simulation studies (morphological, robust, and double target analyses) and an in vivo experiment were performed.

Results

The proposed methods demonstrated morphological accuracy, location accuracy, and reconstruction robustness in glioma simulation studies. An in vivo experiment with an orthotopic glioma mouse model confirmed the advantages of the proposed methods. The proposed methods always yielded the best intersection of union (IoU) in simulations and in vivo experiments (mean of 0.80 IoU).

Conclusions

Simulation studies and in vivo experiments demonstrate that the proposed half-threshold hybrid truncated Laplacian algorithm had an improved performance compared with the comparative algorithm in terms of morphology.

中文翻译：

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荧光分子断层扫描形态重建的非凸拉普拉斯流形接头方法

目的

荧光分子断层扫描 (FMT) 是一种用于小动物生物标志物三维 (3D) 可视化的有前途的技术。形态重建对于 FMT 的进一步应用是有价值和必要的，因为它天生需要了解分子探针分布。

程序

在这项研究中，提出了一个拉普拉斯流形正则化联合ℓ _1/2 -范数模型用于形态重建，并通过通常称为半阈值算法的非凸算法求解。该模型结合结构和稀疏先验来实现目标的位置和结构。此外，为了更好的形态重建，提出了两种改进形式（截断和混合截断形式）。为了平衡重构边界的锐度和平滑度，提出了截断形式。为更多结构先验提出了混合截断形式。为了评估所提出的方法，进行了三个模拟研究（形态学、稳健性和双目标分析）和一个体内实验。

结果

所提出的方法在胶质瘤模拟研究中证明了形态学准确性、定位准确性和重建鲁棒性。原位神经胶质瘤小鼠模型的体内实验证实了所提出方法的优势。所提出的方法总是在模拟和体内实验中产生最佳的联合交集（IoU）（平均 0.80 IoU）。

结论

仿真研究和体内实验表明，与比较算法相比，所提出的半阈值混合截断拉普拉斯算法在形态学方面具有改进的性能。