TY - JOUR
T1 - Detecting task-based fMRI compliance using plan abandonment techniques
AU - Pereira, Ramon Fraga
AU - Heinsfeld, Anibal Sólon
AU - Franco, Alexandre Rosa
AU - Buchweitz, Augusto
AU - Meneguzzi, Felipe
N1 - Acknowledgements
Report From 2015 Biainhack Americas (MX). The authors would like to thank the organizers and attendees of Brainhack MX and the developers of AFNI.
PY - 2016/11
Y1 - 2016/11
N2 - Task-based fMRI is a powerful approach to understand brain processes for a certain task. However, fMRI images are usually preprocessed hours, days or even months after the scan. During the functional image preprocessing stage, defects in images are detected and, in some cases, cannot be corrected. For example, technical problems with the scanner or lack of collaboration from the subject to perform the given tasks. For these cases it is necessary to realize a new scan. In order to mitigate lost scans due to patient non-compliance, we need an approach to detect such non-compliance during the scan.
AB - Task-based fMRI is a powerful approach to understand brain processes for a certain task. However, fMRI images are usually preprocessed hours, days or even months after the scan. During the functional image preprocessing stage, defects in images are detected and, in some cases, cannot be corrected. For example, technical problems with the scanner or lack of collaboration from the subject to perform the given tasks. For these cases it is necessary to realize a new scan. In order to mitigate lost scans due to patient non-compliance, we need an approach to detect such non-compliance during the scan.
U2 - 10.1186/s13742-016-0147-0-s
DO - 10.1186/s13742-016-0147-0-s
M3 - Article
VL - 5
JO - Gigascience
JF - Gigascience
IS - S1
M1 - A19
ER -