fMRI activation detection by obtaining BOLD response of extracted balloon parameters with Particle Swarm Optimization

Taalimi Ali, Fatemizadeh Emad
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引用次数: 1

Abstract

Functional magnetic resonance imaging (fMRI) has immense worth in neuroimaging. The basic techniques used in fMRI data analysis were founded on a linear time-invariant system depicted with the impulse response function (HDR). However, there are evidences which accept nonlinear relations between the measured BOLD response and the task, especially in the case of rapid stimulation. Physiological models are replaced with previous impulse response function and use information based on physiological concept. In this paper, balloon model parameters as a physiological model were extracted using particle swarm optimization and then difference between obtained BOLD response from these parameters and measured signal from fMRI, were used to detect the active region.
利用粒子群算法对提取的气球参数进行BOLD响应的fMRI激活检测
功能磁共振成像(fMRI)在神经影像学中具有巨大的应用价值。fMRI数据分析的基本技术是建立在脉冲响应函数(HDR)描述的线性时不变系统上的。然而,有证据表明实测的BOLD反应与任务之间存在非线性关系,特别是在快速刺激的情况下。用脉冲响应函数代替以往的生理模型,利用基于生理概念的信息。本文采用粒子群优化方法提取球囊模型参数作为生理模型,利用这些参数得到的BOLD响应与fMRI测量信号的差值进行活跃区检测。
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