L(p) regularization for early gate fluorescence molecular tomography.
L(p) regularization for early gate fluorescence molecular tomography.
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DOI：
10.1364/ol.39.004156
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发表时间：
2014-07-15
期刊：
影响因子：
3.6
通讯作者：
Intes X
中科院分区：
文献类型：
--
作者：
Zhao L;Yang H;Cong W;Wang G;Intes X
时域荧光分子断层扫描（TD-FMT）提供了一个独特的数据集，增强定量和空间分辨率。时间门数据集可以在最大计数门周围分为两个时间组，即早门和晚门。已经确定的是，早期门允许提高空间分辨率，晚期门对于荧光团解混和浓度定量是必不可少的。然而，FMT的逆问题是病态的和典型的欠定，这使得图像重建非常容易受到数据噪声。更具体地，由于组织的高吸收和散射，光子计数在早期门处固有地非常低，导致低信噪比和不稳定的重建。在这项工作中，Lp正则化为基础的重建算法的开发和测试与我们的宽场网格为基础的Monte Carlo模拟策略。我们比较了从模拟肾脏荧光团吸收的合成小鼠模型和临床前数据中使用不同p（p ∈ {1/16，1/8，1/4，1/3，1/2，1，2}）获得的早期时间门重建。从一个3D小鼠图谱和小鼠实验的结果表明，我们的L1/4正则化方法提供了最好的性能，为早期的时间门重建。
Time domain fluorescence molecular tomography (TD-FMT) provides a unique dataset for enhanced quantification and spatial resolution. The time-gate dataset can be divided into two temporal groups around the maximum counts gate, which are early gates and late gates. It is well established that early gates allow for improved spatial resolution and late gates are essential for fluorophore unmixing and concentration quantification. However, the inverse problem of FMT is ill-posed and typically underdetermined, which makes image reconstruction highly susceptible to data noise. More specifically, photon counts are inherently very low at early gates due to high absorption and scattering of tissue, resulting in a low signal-to-noise ratio and unstable reconstructions. In this work, an Lp regularization-based reconstruction algorithm was developed and tested with our wide-field mesh-based Monte Carlo simulation strategy. We compared the early time-gate reconstructions obtained with the different p (p ∈ {1/16, 1/8, 1/4, 1/3, 1/2, 1, 2}) from a synthetic murine model simulating the fluorophore uptake in the kidneys and preclinical data. The results from a 3D mouse atlas and a mouse experiment show that our L1/4 regularization methods give the best performance for early time gates reconstructions.