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Beyond filtered backprojection: a reconstruction software package for ion beam microtomography data

机译:超越滤波反投影:用于离子束显微断层扫描数据的重建软件包

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摘要

A new version of the TomoRebuild data reduction software package is presented, for the reconstruction of scanning transmission ion microscopy tomography (STIMT) and particle induced X-ray emission tomography (PIXET) images. First, we present a state of the art of the reconstruction codes available for ion beam microtomography. The algorithm proposed here brings several advantages. It is a portable, multi-platform code, designed in C++ with well-separated classes for easier use and evolution. Data reduction is separated in different steps and the intermediate results may be checked if necessary. Although no additional graphic library or numerical tool is required to run the program as a command line, a user friendly interface was designed in Java, as an ImageJ plugin. All experimental and reconstruction parameters may be entered either through this plugin or directly in text format files. A simple standard format is proposed for the input of experimental data. Optional graphic applications using the ROOT interface may be used separately to display and fit energy spectra. Regarding the reconstruction process, the filtered backprojection (FBP) algorithm, already present in the previous version of the code, was optimized so that it is about 10 times as fast. In addition, Maximum Likelihood Expectation Maximization (MLEM) and its accelerated version Ordered Subsets Expectation Maximization (OSEM) algorithms were implemented. A detailed user guide in English is available. A reconstruction example of experimental data from a biological sample is given. It shows the capability of the code to reduce noise in the sinograms and to deal with incomplete data, which puts a new perspective on tomography using low number of projections or limited angle.
机译:提出了新版本的TomoRebuild数据缩减软件包,用于重建扫描透射离子显微镜断层扫描(STIMT)和粒子诱导X射线断层扫描(PIXET)图像。首先,我们介绍了可用于离子束显微断层扫描的重建代码的最新技术水平。这里提出的算法带来了几个优点。它是一种可移植的,多平台的代码,使用C ++设计,具有良好分隔的类,以便于使用和演化。数据缩减分为不同的步骤,如有必要,可以检查中间结果。尽管不需要其他图形库或数字工具即可将程序作为命令行运行,但使用Java设计了用户友好界面作为ImageJ插件。所有实验和重建参数都可以通过此插件输入,也可以直接在文本格式文件中输入。提出了一种用于输入实验数据的简单标准格式。使用ROOT界面的可选图形应用程序可单独用于显示和拟合能谱。关于重建过程,已在代码的先前版本中存在的滤波反投影(FBP)算法经过优化,以使其速度提高了约10倍。此外,还实现了最大似然期望最大化(MLEM)及其加速版本的有序子集期望最大化(OSEM)算法。提供英文的详细用户指南。给出了来自生物样品的实验数据的重建实例。它显示了代码减少正弦图中的噪声并处理不完整数据的能力,这为使用少量投影或有限角度的层析成像技术提供了新的视角。

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