Glatard Tristan, Lewis Lindsay B, Ferreira da Silva Rafael, Adalat Reza, Beck Natacha, Lepage Claude, Rioux Pierre, Rousseau Marc-Etienne, Sherif Tarek, Deelman Ewa, Khalili-Mahani Najmeh, Evans Alan C
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada ; Centre National de la Recherche Scientifique, University of Lyon, INSERM, CREATIS Villeurbanne, France.
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
Front Neuroinform. 2015 Apr 24;9:12. doi: 10.3389/fninf.2015.00012. eCollection 2015.
Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed.
众所周知，神经成像流程会因编译和执行它们的计算平台不同而产生不同的结果。我们使用三个主要的神经成像软件包（FSL、FreeSurfer和CIVET）以及不同版本的GNU/Linux，对脑组织分类、功能磁共振成像（fMRI）分析和皮质厚度（CT）提取中的这些差异进行了量化。我们还通过库和系统调用拦截来确定这些差异的一些原因。我们发现，这些软件包使用基于单精度浮点运算的数学函数，而操作系统中这些函数的实现仍在不断发展。虽然这些差异对诸如脑提取和皮质组织分类等简单分析流程影响很小或没有影响，但它们的累积在诸如皮质下组织分类、fMRI分析和皮质厚度提取等较长流程中产生了重要差异。使用FSL时，在不同操作系统上获得的皮质下分类之间的大多数骰子系数仍高于0.9，但也观察到低至0.59的值。由于运动校正的差异，在三分之一的测试对象中，fMRI数据的独立成分分析（ICA）在不同操作系统之间存在差异。使用FreeSurfer和CIVET时，在某些脑区，我们发现构建版本或操作系统对皮质厚度有影响。纠正这些可重复性问题的第一步是在流程的关键部分使用更精确的浮点数表示。还应审查流程的数值稳定性。
