Many research applications of neuroimaging use magnetic resonance imaging (MRI). As such, recommendations for image analysis and standardized imaging pipelines exist. Clinical imaging, however, relies heavily on X-ray computed tomography (CT) scans for diagnosis and prognosis. Currently, there is only one image processing pipeline for head CT, which focuses mainly on head CT data with lesions. We present tools and a complete pipeline for processing CT data, focusing on open-source solutions, that focus on head CT but are applicable to most CT analyses. We describe going from raw DICOM data to a spatially normalized brain within CT presenting a full example with code. Overall, we recommend anonymizing data with Clinical Trials Processor, converting DICOM data to NIfTI using dcm2niix, using BET for brain extraction, and registration using a publicly-available CT template for analysis.

中文翻译：

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处理头部 CT 数据的建议

神经成像的许多研究应用使用磁共振成像 (MRI)。因此，存在对图像分析和标准化成像管道的建议。然而，临床成像在很大程度上依赖于 X 射线计算机断层扫描 (CT) 扫描来进行诊断和预后。目前头部CT的图像处理流水线只有一个，主要针对有病灶的头部CT数据。我们提供用于处理 CT 数据的工具和完整的管道，专注于开源解决方案，专注于头部 CT 但适用于大多数 CT 分析。我们描述了从原始 DICOM 数据到 CT 中空间归一化大脑的过程，展示了一个带有代码的完整示例。总的来说，我们建议使用 Clinical Trials Processor 匿名化数据，使用 dcm2niix 将 DICOM 数据转换为 NIfTI，使用 BET 进行大脑提取，