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Abstract #1646

Automatic physiological noise estimator with PESTICA in HCP resting state fMRI data

Wanyong Shin1, Erik Beall1, and Mark J Lowe1

1Radiology, Cleveland Clinic, Cleveland, OH, United States

Recent work with accelerated HCP rs-fMRI data shows strong correlation with non-neuronal noise sources, and their noise patterns appears to be linked across simultaneously excited slices (SMS)1,2. To correct for these noise sources, a measurement of physiologic cycles is needed, which can be supplied by monitoring, but not always available or accurate, or PESTICA which estimates physiological signal fluctuation from EPI data itself3. If the noise is dependent on SMS location, PESTICA could more efficiently detect physiologic signal fluctuation in HCP fMRI. In this study, we modified PESTICA for the SMS acuisition and evaluated performance compared with monitored physiological signals

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