Wavelet-Based Statistical Analysis versus SPM of Brain Imaging Data
نویسنده
چکیده
Analysis of functional magnetic resonance imaging (fMRI) data of a block-based visual stimulation paradigm was comparatively performed by the discrete wavelet transform (DWT) in the wavelet domain and statistical parametric mapping (SPM) within the framework of the general linear model (GLM) [1]. The link is supported by the low-pass analysis filter of the DWT that can be similarly shaped to a Gaussian filter in SPM and by the subsampling scheme that provides means to define the number of coefficients in the low-pass subband of the wavelet decomposition [2]. Functional data processing in the wavelet domain was carried out by means of two biorthogonal transforms resulting in activation patterns similar to the activation maps obtained in SPM.
منابع مشابه
Wavelet-Based Statistical Analysis in Functional Neuroimaging
Wavelet-based analysis versus Gaussian smoothing in statistical parametric mapping (SPM) for detecting and analyzing brain activity from functional magnetic resonance imaging (fMRI) data is presented. Detection of activation in fMRI data can be performed in the wavelet domain by a coefficient-wise statistical t-test. The link between the wavelet analysis and SPM is based on two observations: (i...
متن کاملStatistical Parametric Mapping of Functional MRI data Using Spectral Graph Wavelets
In typical statistical parametric mapping (SPM) of fMRI data, the functional data are pre-smoothed using a Gaussian kernel to reduce noise at the cost of losing spatial specificity. Wavelet approaches have been incorporated in such analysis by enabling an efficient representation of the underlying brain activity through spatial transformation of the original, un-smoothed data; a successful fram...
متن کاملSurfing the Brain: An Overview of Wavelet-Based Techniques for fMRI Data Analysis
Over the past 10 years, many wavelet-based techniques have emerged for the analysis of fMRI data. Indeed, the wavelet transform has many interesting properties for fMRI data analysis: multi-resolution representation; the ability to provide sparse representations of typical brain activation maps; approximately decorrelated wavelet coefficients. In this paper, we give an overview of wavelet-based...
متن کاملAnatomically-adapted graph wavelets for improved group-level fMRI activation mapping
A graph based framework for fMRI brain activation mapping is presented. The approach exploits the spectral graph wavelet transform (SGWT) for the purpose of defining an advanced multi-resolutional spatial transformation for fMRI data. The framework extends wavelet based SPM (WSPM), which is an alternative to the conventional approach of statistical parametric mapping (SPM), and is developed spe...
متن کاملROC evaluation of statistical wavelet-based analysis of brain activation in [15O]-H2O PET scans.
This paper presents and evaluates a wavelet-based statistical analysis of PET images for the detection of brain activation areas. Brain regions showing significant activations were obtained by performing Student's t tests in the wavelet domain, reconstructing the final image from only those wavelet coefficients that passed the statistical test at a given significance level, and discarding artif...
متن کامل