在健康和疾病中的体内大脑磁共振光谱的元分析和开源数据库
Aaron T Gudmundson1, Annie Koo2, Anna Virovka2
1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
Analytical biochemistry
|July 9, 2023
概括
这项研究确定了大脑代谢产物的生理范围. 这些发现有助于验证磁共振光谱 (MRS) 数据模拟和开发用于神经科学研究的先进机器学习算法.
科学领域:
- 神经科学是一个神经科学.
- 生物物理学的生物物理.
- 医疗成像医学成像
背景情况:
- 质子 (1H) 磁共振光谱 (MRS) 是一种关键的非侵入性技术,用于体内脑代谢物量化.
- 标准化工作已经推进了MRS,但使用地面真相数据进行方法验证仍然是一个挑战.
- 数据模拟对于验证MRS方法至关重要,特别是开发机器学习算法,但定义准确的模拟参数是困难的.
结论:
- 这项工作通过提供经过验证的代谢物范围来解决MRS中可靠的基准真实数据的需求.
- 这些发现支持开发更准确的机器学习模拟和神经科学中的深度学习应用.
- 建立的范围是MRS领域数据模拟和方法验证的基本参考估计.
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