Importance of realignment parameters in fMRI data analysis

Zafar, R. and Malik, A.S. and Kamel, N. and Dass, S.C. (2016) Importance of realignment parameters in fMRI data analysis. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Functional magnetic resonance imaging (fMRI) is one of the finest modality to measure brain activity. Two main steps in the analysis of fMRI data are pre-processing and the statistical analysis. Pre-processing is equally an important part because it takes raw data from the scanner and prepares it for the statistical analysis. This study first explains the realignment during preprocessing and then the importance of realignment parameters (one of nuisance parameters) in General Linear model (GLM). Nuisance regressors are used to reduce noise only and are effect of no interest. In this study, it is concluded that realignment parameters have a significant effect in the model estimation because the results are improved with these parameters especially when large head movement is found during data acquisition. © 2015 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 2; Conference of 4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015 ; Conference Date: 19 October 2015 Through 21 October 2015; Conference Code:119504
Uncontrolled Keywords: Brain; Data acquisition; Data handling; Functional neuroimaging; Magnetic resonance imaging; Noise pollution; Statistical methods, fMRI; fMRI data analysis; Functional magnetic resonance imaging; General linear modeling; Model estimation; Nuisance parameter; Nuisance regressors; Realignment, Image processing
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:18
Last Modified: 09 Nov 2023 16:18
URI: https://khub.utp.edu.my/scholars/id/eprint/7175

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