Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
|Place of Conferral||中国科学院自动化研究所|
1. 基于光源空间分布特性的光学分子断层成像方法。通过将光源空间稀疏分布先验知识引入光学分子断层成像，构建了基于稀疏重建理论的光学分子断层成像方法。在稀疏重建理论中，一般包含两类重建策略：贪婪策略与迭代优化策略。本文一方面在传统贪婪策略的基础上，研究了基于前向预测正交匹配追踪的光学分子断层成像方法，通过在原子筛选中引入前向预测函数，对进入支撑集原子进行更加谨慎地评估，减小原子误选概率，从而提升重建精度；另一方面，在传统迭代优化策略基础上，研究了基于非负迭代凸优化的光学分子断层成像新方法，引入spike and slab先验模型构建非凸目标函数，将其分解为若干个凸优化子问题进行迭代求解，获得原问题的解。通过系列数值仿真实验与活体乳腺肿瘤成像实验验证了方法的有效性。
Molecular imaging is a new generation of specific medical imaging technology that combines multiple disciplines such as medicine, informatics, biology, chemistry, and materials science. Compared with traditional imaging technologies, its outstanding feature is that it can perform dynamic in vivo visualization, characterization and quantitative researches on the physiological changes of humans and other life systems at the molecular and cellular level. It has been widely used in early diagnosis of diseases, image-guided survey, evaluation of drug efficacy, etc. As an important part of the molecular imaging methods, optical molecular tomography (OMT) utilizes the molecular probes, which emit the optical signals to obtain the three-dimensional spatial distribution of in vivo specific cell molecules and to provide the quantitative indicators for the related physiological processes. With the advantages of high sensitivity, good specificity, and low cost, OMT has a rapid development in the past ten years. A large number of research results on OMT have been obtained in the field of biomedical imaging. However, the photon transmission process in biological tissues is extremely complicated, especially the severe scattering effect, which makes OMT a highly ill-conditioned problem. The imaging performance of OMT faces great challenges, which are embodied in the constraint of the location accuracy, the shape recovery capability, and the imaging robustness.
To improve the imaging accuracy of OMT, several OMT methods are researched in this thesis based on the distribution characteristics of optical sources. The performance of these methods is validated via the numerical simulations and the in vivo tumor-bearing mice model imaging experiments. Firstly, the sparse prior of optical sources is induced in the process of OMT based on the spatial distribution characteristics. Accordingly, two sparse reconstruction methods of OMT are researched based on the greedy strategy and the iterative optimization strategy, respectively. Secondly, the photon transmission process in the novel near-infrared-II (NIR-II) window in different biological tissues is studied based on the spectral distribution characteristics. Accordingly, the tissue-specific forward model for NIR-II fluorescence molecular tomography (FMT) is established and the Gaussian weighted neighborhood fused lasso approach is developed to solve the inverse problem. Lastly, we construct a novel near-infrared-II/near-infrared-I (NIR-II/NIR-I) FMT system, creating great conditions for the applications of the researched OMT methods in the small animal studies. Specifically, the main contents of this thesis are listed as follows:
1. The OMT methods based on the spatial distribution characteristics of optical sources. Two sparse reconstruction methods for OMT are developed by inducing the sparse prior of optical sources in the process of OMT. In the theory of sparse reconstruction, there exist two types of reconstruction strategies, including the greedy strategy and the iterative reconstruction strategy. On the one hand, based on the greedy strategy, the look ahead orthogonal matching pursuit based OMT method is developed, which utilizes a look ahead function for more careful evaluation of the atoms in the support set to enhance the reconstruction accuracy. On the other hand, based on the iterative optimization strategy, the non-negative iterative convex refinement based OMT method is developed by inducing the spike and slab prior. Using this prior, a non-convex objective function is obtained, which can be decomposed into a series of convex sub-problems to approach the solution of original problem iteratively. To verify the performance of these methods, several numerical simulations and in vivo breast cancer imaging experiments are conducted.
2. The OMT method based on the spectral distribution characteristics of optical sources. Firstly, the transmission characteristics of NIR-II photons are studied with the Monte Carlo photon simulations and the mice vessel imaging experiments, which validate the advantages of NIR-II fluorescence imaging. The tissue-specific forward model of NIR-II FMT is established by combining the optical characteristics of NIR-II fluorescence and the diffusion equation. A Gaussian weighted neighborhood fused lasso approach is proposed to solve the inverse problem of NIR-II FMT. Finally, the effectiveness of this method is verified via several experiments such as single-source simulation, dual-source simulation, in vivo tumor imaging, and deep source imaging.
3. A novel NIR-II/NIR-I FMT system, which creates great conditions for the applications of the proposed OMT methods in the small-animal experiments. In vivo experiments are the important standard to evaluate the OMT methods and the ultimate goal of the OMT researches. This thesis introduces the structure and the data acquisition process of the NIR-II/NIR-II FMT system. Diversities of in vivo imaging experiments are designed to verify the in vivo applicability of the proposed OMT methods, which provides new ideas for the transformation of OMT.
|蔡美山. 基于光源分布特性的小动物光学分子断层成像方法研究[D]. 中国科学院自动化研究所. 中国科学院大学,2021.|
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