为了克服传统轴棱锥产生太赫兹贝塞尔光束无衍射距离短的局限，设计了一种双锥面轴棱锥结构。基于几何光学理论对双锥面轴棱锥产生太赫兹贝塞尔光束的原理进行了分析，并对太赫兹贝塞尔光束的无衍射特性和双锥面轴棱锥顶点对齐误差对无衍射特性的影响进行了理论和仿真计算分析。同时，采用透射式太赫兹时域光谱系统对双锥面轴棱锥的功能进行了实验验证。仿真和实验结果表明：太赫兹波经过锥面底角为γ₂=20°、γ₁=15°的双锥面轴棱锥后能够产生110 mm无衍射距离的太赫兹贝塞尔光束，相较于传统轴棱锥，无衍射距离增加了82.63 mm；无衍射距离随着锥形底面角度的增加而增大。

Bioluminescence tomography (BLT) is a promising imaging modality that can provide noninvasive three-dimensional visualization information on tumor distribution. In BLT reconstruction, the widely used methods based on regularization or greedy strategy face problems such as over-sparsity, over-smoothing, spatial discontinuity, poor robustness, and poor multi-target resolution. To deal with these problems, combining the advantages of the greedy strategies as well as regularization methods, we propose a hybrid reconstruction framework for model-based multispectral BLT using the support set of a greedy strategy as a feasible region and the Alpha-divergence to combine the weighted solutions obtained by L1-norm and L2-norm regularization methods. In numerical simulations with digital mouse and in vivo experiments, the results show that the proposed framework has better localization accuracy, spatial resolution, and multi-target resolution.Bioluminescence tomography (BLT) is a promising imaging modality that can provide noninvasive three-dimensional visualization information on tumor distribution. In BLT reconstruction, the widely used methods based on regularization or greedy strategy face problems such as over-sparsity, over-smoothing, spatial discontinuity, poor robustness, and poor multi-target resolution. To deal with these problems, combining the advantages of the greedy strategies as well as regularization methods, we propose a hybrid reconstruction framework for model-based multispectral BLT using the support set of a greedy strategy as a feasible region and the Alpha-divergence to combine the weighted solutions obtained by L1-norm and L2-norm regularization methods. In numerical simulations with digital mouse and in vivo experiments, the results show that the proposed framework has better localization accuracy, spatial resolution, and multi-target resolution.

为克服生物发光断层成像(BLT)的不适定性,获得稳定的光源重建结果,本文提出了一种基于连续化原对偶有效集(PDASC)的多光谱BLT重建算法,该算法将原对偶有效集算法(PDAS)与连续化技术相结合,可以自动调节正则化参数,从而获得全局最优解。多组数字鼠仿真实验验证了该算法的有效性和稳定性,且与原对偶有效集算法、硬阈值追踪法(HTP)相比,所提PDASC重建算法在不同光源设置下的各量化指标均表现更优,在体小鼠实验结果进一步证明了该算法在实际应用中的潜力。

提出将百分位半阈值匹配追踪法(PHTPA)应用于生物发光断层成像(BLT)这一光学分子成像模态领域。将BLT光源重建为一个L1/2范数正则化问题,在迭代半阈值算法(HTA)的基础上,结合子空间跟踪和百分位阈值法对其求解。在数字鼠模型上设计多组仿真实验,对改进的半阈值算法进行有效性和收敛性的评估。仿真结果表明,与原有的HTA和迭代重赋权算法相比,PHTPA在不同光源设置下都能得到更为准确的重建结果。

Bioluminescence tomography (BLT) is an important noninvasive optical molecular imaging modality in preclinical research. To improve the image quality, reconstruction algorithms have to deal with the inherent ill-posedness of BLT inverse problem. The sparse characteristic of bioluminescent sources in spatial distribution has been widely explored in BLT and many L1-regularized methods have been investigated due to the sparsity-inducing properties of L1 norm. In this paper, we present a reconstruction method based on L1=2 regularization to enhance sparsity of BLT solution and solve the nonconvex L1=2 norm problem by converting it to a series of weighted L1 homotopy minimization problems with iteratively updated weights. To assess the performance of the proposed reconstruction algorithm, simulations on a heterogeneous mouse model are designed to compare it with three representative sparse reconstruction algorithms, including the weighted interior-point, L1 homotopy, and the Stagewise Orthogonal Matching Pursuit algorithm. Simulation results show that the proposed method yield stable reconstruction results under different noise levels. Quantitative comparison results demonstrate that the proposed algorithm outperforms the competitor algorithms in location accuracy, multiple-source resolving and image quality.

生物发光断层成像(BLT)是利用生物体表面光强信息,重建出荧光光源在生物体内三维分布的一种新兴光学分子影像技术。由于生物体表面的测量信息有限,并且生物体内组织结构复杂,BLT的光源重建有着严重的病态性。为提高光源重建质量,提出了一种结合可行域收缩策略的多级自适应有限元光源重建方法。为了评估该方法的光源定位能力和能量密度定量能力,在数字鼠模型上分别设计了单光源和双光源实验。结果表明,本文方法可以显著提高光源的定位精度和能量密度。

生物发光断层成像(BLT)是一种低成本、高灵敏、具有巨大潜力的光学分子成像模态，高效稳定的重建算法是将其推向实用的关键。为克服BLT重建的高不适定性，提出了基于非凸L1-2正则化的重建方法，采用凸差分算法来解决非凸泛函最小化问题，在每一步迭代中采用带自适应惩罚项的交替方向乘子法高效求解。为评估该方法的有效性和稳健性，设计了单光源和双光源数字鼠仿体实验，并与3个典型的重建算法进行对比，仿真实验结果表明，所提L1-2正则化方法在不同光源设置下都得到了最准确的光源定位。

As an emerging molecular imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) uses X-ray-excitable probes to produce near-infrared (NIR) luminescence and then reconstructs three-dimensional (3D) distribution of the probes from surface measurements. A proper photon-transportation model is critical to accuracy of XLCT. Here, we presented a systematic comparison between the common-used Monte Carlo model and simplified spherical harmonics (SPN). The performance of the two methods was evaluated over several main spectrums using a known XLCT material. We designed both a global measurement based on the cosine similarity and a locally-averaged relative error, to quantitatively assess these methods. The results show that the SP3 could reach a good balance between the modeling accuracy and computational e±ciency for all of the tested emission spectrums. Besides, the SP1 (which is equivalent to the diffusion equation (DE)) can be a reasonable alternative model for emission wavelength over 692 nm. In vivo experiment further demonstrates the reconstruction performance of the SP3 and DE. This study would provide a valuable guidance for modeling the photon-transportation in CB-XLCT.

生物发光断层成像(BLT)是一种高灵敏度、高特异性的光学分子影像技术，可根据探测到的生物体表光强来重建发光光源在生物体内的三维分布。由于生物体表面测得的光强信息有限，光源重建面临巨大的挑战。为了在有限的测量条件下获得更精确的重建光源，结合BLT中光源稀疏分布的特征，将重建问题转化为L1范数优化问题，并采用迭代支撑检测(ISD)算法实现快速重建，该算法交替执行支撑集检测和信号重构两个模块，直至重建精度达到要求。为了评估ISD算法的光源定位能力，设计数字鼠仿真实验，并与三种典型的稀疏重建算法比较。仿真结果表明ISD算法对于单光源和双光源目标均可以实现准确的重建。

Fluorescence molecular tomography (FMT) allows the detection and quantification of various biological processes in small animals in vivo, which expands the horizons of pre-clinical research and drug development. Efficient three-dimensional (3D) reconstruction algorithm is the key to accurate localization and quantification of fluorescent target in FMT. In this paper, 3D reconstruction of FMT is regarded as a sparse signal recovery problem and the compressive sampling matching pursuit (CoSaMP) algorithm is adopted to obtain greedy recovery of fluorescent signals. Moreover, to reduce the modeling error, the simplified spherical harmonics approximation to the radiative transfer equation (RTE), more specifically SP₃, is utilized to describe light propagation in biological tissues. The performance of the proposed reconstruction method is thoroughly evaluated by simulations on a 3D digital mouse model by comparing it with three representative greedy methods including orthogonal matching pursuit (OMP), stagewise OMP (StOMP), and regularized OMP (ROMP). The CoSaMP combined with SP₃ shows an improvement in reconstruction accuracy and exhibits distinct advantages over the comparative algorithms in multiple targets resolving. Stability analysis suggests that CoSaMP is robust to noise and performs stably with reduction of measurements. The feasibility and reconstruction accuracy of the proposed method are further validated by phantom experimental data.