Mathematical Sciences: Improved Statistical Methods for Magnetic Resonance Spectroscopy

数学科学：改进的磁共振波谱统计方法

• 批准号: 9116730
• 负责人: Jonathan Raz
• 金额: $ 4.57万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1994-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9116730&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Improved; Statistical; Methods

Magnetic resonance spectra, used in scientific, engineering and medical research, depart from pure Lorentzian behavior in the presence of inhomogeneities such as those commonly encountered in many of these applications. This research will develop appropriate analytic methods using statistical theory drawn from semiparametric model analysis. This new methodology will be derived to remove distortions caused by magnetic field inhomogeneity and by temporal instability. Also, statistical theory and methodology will be developed to analyze repeated observations such as those taken to identify and study metabolic changes at intervals during an extended period of time.

在科学、工程和医学研究中使用的磁共振谱，在存在非均质性的情况下，偏离了纯洛伦兹行为，例如在许多这些应用中经常遇到的那些非均质性。本研究将利用半参数模型分析的统计理论，发展适当的分析方法。这种新方法将用于消除由磁场不均匀性和时间不稳定性引起的畸变。此外，将发展统计理论和方法来分析重复的观察结果，例如在一段较长的时间间隔内确定和研究代谢变化的观察结果。