Choice of data types in time resolved fluorescence enhanced diffuse optical tomography.
Choice of data types in time resolved fluorescence enhanced diffuse optical tomography.
复制标题
时间分辨荧光增强漫射光学断层扫描数据类型的选择。
DOI：
10.1118/1.2804775
复制
发表时间：
2007
期刊：
影响因子：
3.8
通讯作者：
Gandjbakhche,Amir
中科院分区：
文献类型：
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作者：
Riley,Jason;Hassan,Moinuddin;Chernomordik,Victor;Gandjbakhche,Amir
在本文中，我们研究可能的数据类型的时间分辨荧光增强扩散光学层析成像（FDOT）。FDOT是扩散光学层析成像的一个特例，我们的目标是分析深深嵌入混浊介质中的荧光团。我们专注于不同的数据类型集的相对鲁棒性噪声。我们使用一个分析模型来生成预期的时间点扩散函数（TPSF），并从中生成数据类型。在生成数据类型之前，将不同级别的噪声应用于TPSF。我们表明，本地数据类型比全球数据类型更强大的噪声，并应提供增强的信息的逆问题。我们继续表明，与一个简单的重建算法，深度和寿命（感兴趣的参数）的荧光团更好地重建使用本地数据类型。此外，我们还证明了深度和生存期之间的关系对于局部数据类型来说更好地保持了，这表明它们在某种程度上不仅更鲁棒，而且也是自正则化的。我们的结论是，虽然在一般情况下，本地数据类型的生成成本可能更高，但它们确实比标准的全局数据类型提供了明显的优势。
In this paper we examine possible data types for time resolved fluorescence enhanced diffuse optical tomography (FDOT). FDOT is a particular case of diffuse optical tomography, where our goal is to analyze fluorophores deeply embedded in a turbid medium. We focus on the relative robustness of the different sets of data types to noise. We use an analytical model to generate the expected temporal point spread function (TPSF) and generate the data types from this. Varying levels of noise are applied to the TPSF before generating the data types. We show that local data types are more robust to noise than global data types, and should provide enhanced information to the inverse problem. We go on to show that with a simple reconstruction algorithm, depth and lifetime (the parameters of interest) of the fluorophore are better reconstructed using the local data types. Further we show that the relationship between depth and lifetime is better preserved for the local data types, suggesting they are in some way not only more robust, but also self‐regularizing. We conclude that while the local data types may be more expensive to generate in the general case, they do offer clear advantages over the standard global data types.