Statistical Analysis Of Image Features

图像特征统计分析

• 批准号: 7591914
• 负责人: Daniel W Hommer
• 金额: $ 47.07万
• 依托单位: NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7591914
• 关键词: Accounting; Age; Alcohol consumption; Alcohols; Blood flow; Blur; Brain; Brain region; Complex; Condition; Data; Development; Diagnostic; Emotions; Experimental Designs; Fourier Transform; Functional Magnetic Resonance Imaging; Image; Image Analysis; Individual; Intake; Investigation; Linear Models; Localized; Magnetic Resonance Imaging; Measures; Methodology; Methods; Noise; Numbers; Outcome; Pharmaceutical Preparations; Positron-Emission Tomography; Property; Research; Series; Signal Transduction; Simulate; Slide; Statistical Methods; Stimulus; Structure; Techniques; Testing; Time; Time Series Analysis; alcohol craving; base; design; experience; hemodynamics; interest; problem drinker; research study; response; statistics; theories; visual stimulus

Three different statistical methods have been developed, based on the Fourier transform, the wavelet transform, and the theory of Gaussian random fields in the spatial domain. All three methods have been applied to the analysis of PET and MR images from normal and alcoholic subjects and have identified significant differences in generally the same brain regions. Current research on these topics includes the development of a 1-D Gaussian random field method to analyze fMRI time series data. This methodology can be used to analyze fMRI data acquired from experiments designed to incorporate a long (that is long enough, as determined experimentally, to estimate the variance associated with the acquired data) baseline condition and transition to another activated state such as one produced by drug or alcohol administration. It uses the long baseline data to estimate the variance measure associated with the temporal data from a voxel within the image and sets a statistically rigorous threshold for activation in spite of the known temporal correlation in the data. This analysis technique is being validated with simulated and experimental data. Furthermore, this analysis technique is being incorporated into numerous experiments including one designed to look at the blood flow changes in the brain associated with alcoholic intake in normal subjects. This presents an ideal demonstration of this analysis technique to basically establish a response curve for alcohol intake. Finally, statistical analysis in the temporal domain based on traditional time series analysis in the Fourier domain have been developed and given similar results in terms of localization of the signal in fMRI blood flow studies to other less rigorous and generalizable techniques. This analysis methodology has the potential to (1) localize fMRI activation changes, (2) estimate or reconstruct the activated signal without the associated noise, (3) estimate the hemodynamic response function locally without prior assumptions as to its structure, and (4) detect multiple responses to multiple input stimuli. Currently this technique is being used to study experimental designs including slides of visual stimuli designed to elicit different emotions or alcohol craving. Furthermore this technique has been extended to incorporate a full complex general linear model (required in the Fourier domain for statistical testing) with up to five inputs stimuli (separately or in combinations). Further development will allow statistical comparison of multiple voxels allowing analysis for example of experiments under different conditions (drug/no-drug) within the context of this general linear model.

三种不同的统计方法已经开发，基于傅立叶变换，小波变换，高斯随机场理论在空间域中。所有这三种方法已被应用于分析PET和MR图像从正常和酗酒的主题，并确定了显着差异，在一般相同的大脑区域。目前对这些问题的研究包括发展一个1-D高斯随机场方法来分析功能磁共振成像时间序列数据。这种方法可用于分析从实验中获得的fMRI数据，该实验设计为结合长（即足够长，如实验所确定的，以估计与所获得的数据相关的方差）基线条件并过渡到另一种激活状态，如药物或酒精管理所产生的激活状态。它使用长基线数据来估计与来自图像内的体素的时间数据相关联的方差测量，并且尽管数据中的已知时间相关性，但是为激活设置统计上严格的阈值。这种分析技术正在验证与模拟和实验数据。此外，这种分析技术正在被纳入许多实验中，包括一项旨在观察正常受试者与酒精摄入相关的大脑血流变化的实验。这提供了该分析技术的理想演示，以基本建立酒精摄入的响应曲线。最后，在傅立叶域中的传统时间序列分析的基础上，在时域中的统计分析已被开发，并给出了类似的结果，在功能磁共振成像血流研究中的信号的本地化，以其他不太严格和概括的技术。这种分析方法具有以下潜力：（1）定位fMRI激活变化，（2）估计或重建激活信号，而没有相关的噪声，（3）估计局部血流动力学响应函数，而无需事先假设其结构，以及（4）检测对多个输入刺激的多个响应。目前，这项技术正被用于研究实验设计，包括旨在引起不同情绪或酒精渴望的视觉刺激幻灯片。此外，这种技术已被扩展到包含一个完整的复杂的一般线性模型（需要在傅立叶域的统计测试）与多达五个输入刺激（单独或组合）。进一步的发展将允许多个体素的统计比较，允许在该一般线性模型的背景下分析例如在不同条件下（药物/无药物）的实验。