Introduction T1-weighted MRI is widely used in clinical neuroimaging for studying brain structure and its changes, including those related to neurodegenerative diseases, and as anatomical reference for analysing other modalities. Ensuring high-quality T1-weighted scans is vital as image quality affects reliability of outcome measures. However, visual inspection can be subjective and time-consuming, especially with large datasets. The effectiveness of automated quality control (QC) tools for clinical cohorts remains uncertain. In this study, we used T1w scans from elderly participants within ageing and clinical populations to test the accuracy of existing QC tools with respect to visual QC and to establish a new quality prediction framework for clinical research use.

中文翻译：

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用于临床研究的 T1 加权脑 MRI 扫描的自动质量控制：质量预测分类器的方法比较和设计

简介T1 加权 MRI 广泛应用于临床神经影像学，用于研究大脑结构及其变化，包括与神经退行性疾病相关的变化，并作为分析其他模式的解剖学参考。确保高质量的 T1 加权扫描至关重要，因为图像质量会影响结果测量的可靠性。然而，目视检查可能是主观且耗时的，尤其是对于大型数据集。自动质量控制（QC）工具对临床队列的有效性仍不确定。在本研究中，我们使用老龄化和临床人群中老年参与者的 T1w 扫描来测试现有 QC 工具在视觉 QC 方面的准确性，并为临床研究使用建立新的质量预测框架。