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磁共振成像数据集与解剖学信托用于质量控制和注册
Alaa Taha1,2, Greydon Gilmore1,2,3, Mohamad Abbass1,3,4
1Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.
Scientific data
|July 12, 2023
概括
这项研究介绍了用于可重现大脑图像注册质量控制的解剖信托 (AFID) 放置. 这些精心策划的数据集增强了神经成像分析,有助于诊断和手术规划.
科学领域:
- 神经成像是一种神经成像.
- 计算神经科学是一种神经科学.
- 医学图像分析 医学图像分析
背景情况:
- 能够重现的,对大脑对应的定量评估至关重要,但有限.
- 之前对解剖学信托 (AFID) 放置协议的验证证明了图像注册评估的毫米精度.
研究的目的:
- 为常用的结构磁共振成像数据集和模板发布精选的解剖学信托配置.
- 为了促进图像注册,神经解剖学教育和临床应用的快速质量控制.
- 为神经成像社区提供一个有价值的资源.
主要方法:
- 在四个数据集 (N=132个受试者,15,232个信托人) 和14个大脑模板 (4,288个信托人) 中,为个体受试者生成了精心策划的AFID安置.
- 标注涉及300多个人类评分器小时.
- 人类评分器的准确性被验证为在1-2毫米以内,使用超过45,000个欧几里德距离测量.
主要成果:
- 针对结构性MRI数据集和模板的AFID安置的综合数据集已经发布.
- 验证的人类评分器对AFID放置的准确性在1-2毫米范围内.
- 发布的数据符合大脑成像数据结构 (BIDS),以便轻松集成到分析管道中.
结论:
- 发布的AFID放置提供了一个标准化工具来评估大脑图像注册的准确性.
- 本资源支持神经解剖学教学,疾病诊断和手术准方面的进展.
- 促进神经成像研究中的可复制和定量分析.
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