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首页> 外文期刊>SoftwareX >TomoPhantom, a software package to generate 2D–4D analytical phantoms for CT image reconstruction algorithm benchmarks
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TomoPhantom, a software package to generate 2D–4D analytical phantoms for CT image reconstruction algorithm benchmarks

机译：TomoPhantom，一个用于生成2D–4D分析体模的软件包，用于CT图像重建算法基准测试

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摘要

In the field of computerized tomographic imaging, many novel reconstruction techniques are routinely tested using simplistic numerical phantoms, e.g. the well-known Shepp–Logan phantom. These phantoms cannot sufficiently cover the broad spectrum of applications in CT imaging where, for instance, smooth or piecewise-smooth 3D objects are common. TomoPhantom provides quick access to an external library of modular analytical 2D/3D phantoms with temporal extensions. In TomoPhantom, quite complex phantoms can be built using additive combinations of geometrical objects, such as, Gaussians, parabolas, cones, ellipses, rectangles and volumetric extensions of them. Newly designed phantoms are better suited for benchmarking and testing of different image processing techniques. Specifically, tomographic reconstruction algorithms which employ 2D and 3D scanning geometries, can be rigorously analyzed using the software. TomoPhantom also provides a capability of obtaining analytical tomographic projections which further extends the applicability of software towards more realistic, free from the “inverse crime” testing. All core modules of the package are written in the C-OpenMP language and wrappers for Python and MATLAB are provided to enable easy access. Due to C-based multi-threaded implementation, volumetric phantoms of high spatial resolution can be obtained with computational efficiency.
机译：在计算机断层摄影成像领域，许多新颖的重建技术通常使用简单的数字体模进行测试，例如著名的Shepp–Logan幻影。这些体模无法充分覆盖CT成像中的广泛应用，在CT成像中，例如常见于光滑或分段光滑的3D对象。通过TomoPhantom，可以快速访问带有时间扩展的模块化2D / 3D分析幻像外部库。在TomoPhantom中，可以使用几何对象（例如高斯，抛物线，圆锥，椭圆，矩形和它们的体积扩展）的加法组合来构建相当复杂的体模。新设计的体模更适合于对不同图像处理技术进行基准测试。具体而言，可以使用该软件严格分析采用2D和3D扫描几何形状的断层图像重建算法。 TomoPhantom还提供了获取分析层析成像投影的功能，从而进一步将软件的适用性扩展到更加现实的状态，而无需进行“反犯罪”测试。软件包的所有核心模块均以C-OpenMP语言编写，并提供了Python和MATLAB的包装器，以方便访问。由于基于C的多线程实现，因此可以高效地获得具有高空间分辨率的体模。

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