基于统计参数映射 (SPM) 和 MATLAB 的功能磁共振成像预处理和质量控制协议。

Frontiers in neuroimaging Pub Date : 2023-01-10 eCollection Date: 2022-01-01 DOI:10.3389/fnimg.2022.1070151
Xin Di, Bharat B Biswal
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摘要

功能磁共振成像(fMRI)已成为研究大脑功能及其在精神和神经疾病中的变化的常用技术。fMRI 研究的样本量一直在稳步增加,越来越多的研究都来自开放存取的脑成像资料库。质量控制对于确保成功的数据处理和有效的统计结果至关重要。在此,我们概述了基于统计参数映射(SPM)和 MATLAB 的 fMRI 数据预处理和质量控制的简单方案。该方案的重点不仅在于识别和移除存在伪影和异常的数据,还在于确保处理过程正确无误。我们将此协议应用于 fMRI 开放质量控制 (QC) 项目的数据,并说明每个质量控制步骤如何帮助识别潜在问题。我们还展示了头骨剥离等简单步骤可以改善功能图像和解剖图像之间的核心配准。
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A functional MRI pre-processing and quality control protocol based on statistical parametric mapping (SPM) and MATLAB.

Functional MRI (fMRI) has become a popular technique to study brain functions and their alterations in psychiatric and neurological conditions. The sample sizes for fMRI studies have been increasing steadily, and growing studies are sourced from open-access brain imaging repositories. Quality control becomes critical to ensure successful data processing and valid statistical results. Here, we outline a simple protocol for fMRI data pre-processing and quality control based on statistical parametric mapping (SPM) and MATLAB. The focus of this protocol is not only to identify and remove data with artifacts and anomalies, but also to ensure the processing has been performed properly. We apply this protocol to the data from fMRI Open quality control (QC) Project, and illustrate how each quality control step can help to identify potential issues. We also show that simple steps such as skull stripping can improve coregistration between the functional and anatomical images.

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