DICOM数据集用于跨制造商和软件版本的可重复的神经成像研究
Christopher Rorden1, Benoît Béranger2, Hu Cheng3
1McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia, SC, 29208, USA. rorden@sc.edu.
Scientific data
|July 9, 2025
概括
本研究介绍了用于可重复的神经成像研究的DICOM数据集. 这些数据集标准化了从CT和MR扫描中提取关键的成像采集参数的提取,无论制造商是谁.
科学领域:
- 医疗成像医学成像
- 神经成像研究研究 神经成像研究
- 数据标准化数据标准化
背景情况:
- 医学数字成像和通信 (DICOM) 是医疗成像数据互操作性的标准.
- 制造商经常使用私有DICOM标签来详细获取参数,从而阻碍了数据的一致性.
- 不断发展的DICOM标准引入了新的公共标签,进一步复杂化了参数提取.
研究的目的:
- 为可复制的神经成像研究创建标准化的DICOM数据集.
- 解决从各种医学成像数据中提取关键获取参数的挑战.
- 为设计用于医学图像数据提取的工具提供验证数据集.
主要方法:
- 开发了CT和MR模式的最小DICOM测试案例.
- 为编码采购细节 (公共,私有标签,专有结构) 提供制造商特定的示例.
- 为每个DICOM数据集提供了相应的NIfTI图像与符合BIDS的JSON元数据.
主要成果:
- 创建了一系列DICOM数据集,展示各种制造商编码实践.
- 在元数据 JSON 文件中确保一致的术语,以减轻编码变化.
- 建立了用于DICOM数据提取工具的验证数据集的存储库.
结论:
- 开发的数据集有助于准确提取可重复性研究的关键成像参数.
- 标准化数据格式 (DICOM,NIfTI,BIDS) 提高了跨制造商数据的一致性.
- 该存储库是验证医疗图像分析工具的宝贵资源.
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