Automated signal drift and global fluctuation removal from 4D fMRI data based on principal component analysis as a major preprocessing step for fMRI data analysis

MLA

Gimi, Barjor, et al. “Automated Signal Drift and Global Fluctuation Removal from 4D FMRI Data Based on Principal Component Analysis as a Major Preprocessing Step for FMRI Data Analysis.” Proceedings of SPIE, vol. 10953, no. 1, Mar. 2019, p. 109531E–109531E–9. EBSCOhost, https://doi.org/10.1117/12.2512968.

APA

Gimi, B., Krol, A., Parmar, H. S., Nutter, B., Long, R., Antani, S., & Mitra, S. (2019). Automated signal drift and global fluctuation removal from 4D fMRI data based on principal component analysis as a major preprocessing step for fMRI data analysis. Proceedings of SPIE, 10953(1), 109531E–109531E–9. https://doi.org/10.1117/12.2512968

Chicago

Gimi, Barjor, Andrzej Krol, Harshit S. Parmar, Brian Nutter, Rodney Long, Sameer Antani, and Sunanda Mitra. 2019. “Automated Signal Drift and Global Fluctuation Removal from 4D FMRI Data Based on Principal Component Analysis as a Major Preprocessing Step for FMRI Data Analysis.” Proceedings of SPIE 10953 (1): 109531E–109531E–9. doi:10.1117/12.2512968.