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Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

Todd N, Josephs O, Callaghan MF, Lutti A, Weiskopf N - Neuroimage (2015)

Bottom Line: Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition.The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction.The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, UK. Electronic address: nicholas.todd@ucl.ac.uk.

No MeSH data available.


Plots of percent reduction in RMSE for PMC On compared to PMC Off as a function of partition-weighted integrated motion. The RMSE data presented in Fig. 7 were averaged over MPW bins that were 2.5 mm wide (only bins with 5 or more data points were used). The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off. Error bars show standard error of the binned RMSE values propagated through the percent difference calculation.
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f0040: Plots of percent reduction in RMSE for PMC On compared to PMC Off as a function of partition-weighted integrated motion. The RMSE data presented in Fig. 7 were averaged over MPW bins that were 2.5 mm wide (only bins with 5 or more data points were used). The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off. Error bars show standard error of the binned RMSE values propagated through the percent difference calculation.

Mentions: Fig. 8 shows percent decrease in RMSE values from PMC off to PMC on cases as a function of MPW. The plots were generated by averaging the data shown in Fig. 7 over bins along the MPW dimension that were 2.5 mm wide. Only bins that had 5 or more data points were kept. The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off, and the error bars show the standard errors of the binned RMSE values propagated through the percent difference calculation. The trend over the data sets showed small percent decreases in RMSE at low levels of motion (MPW < 5 mm), and then greater percent decreases in RMSE as the level of motion rises until a plateau was reached. This plateau in percent decrease of RMSE was larger for the slow motion cases (50%–60%) than for the fast motion cases (~ 40%).


Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

Todd N, Josephs O, Callaghan MF, Lutti A, Weiskopf N - Neuroimage (2015)

Plots of percent reduction in RMSE for PMC On compared to PMC Off as a function of partition-weighted integrated motion. The RMSE data presented in Fig. 7 were averaged over MPW bins that were 2.5 mm wide (only bins with 5 or more data points were used). The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off. Error bars show standard error of the binned RMSE values propagated through the percent difference calculation.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4441089&req=5

f0040: Plots of percent reduction in RMSE for PMC On compared to PMC Off as a function of partition-weighted integrated motion. The RMSE data presented in Fig. 7 were averaged over MPW bins that were 2.5 mm wide (only bins with 5 or more data points were used). The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off. Error bars show standard error of the binned RMSE values propagated through the percent difference calculation.
Mentions: Fig. 8 shows percent decrease in RMSE values from PMC off to PMC on cases as a function of MPW. The plots were generated by averaging the data shown in Fig. 7 over bins along the MPW dimension that were 2.5 mm wide. Only bins that had 5 or more data points were kept. The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off, and the error bars show the standard errors of the binned RMSE values propagated through the percent difference calculation. The trend over the data sets showed small percent decreases in RMSE at low levels of motion (MPW < 5 mm), and then greater percent decreases in RMSE as the level of motion rises until a plateau was reached. This plateau in percent decrease of RMSE was larger for the slow motion cases (50%–60%) than for the fast motion cases (~ 40%).

Bottom Line: Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition.The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction.The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, UK. Electronic address: nicholas.todd@ucl.ac.uk.

No MeSH data available.