Improved map-slice-to-volume motion correction with B0 inhomogeneity correction: validation of activation detection algorithms using ROC curve analyses.
Head motion is a significant source of error in fMRI activation detection and a common approach is to apply 3D volumetric rigid body motion correction techniques. However, in 2D multislice fMRI, each slice may have a distinct set of motion parameters due to inter-slice motion. Here, we apply an automated mutual information based slice-to-volume rigid body registration technique on time series data synthesized from a T2 MRI brain dataset with simulated motion, functional activation, noise and geometric distortion. The map-slice-to-volume (MSV) technique was previously applied to patient data without ground truths for motion and activation regions. In this study, the activation images and area under the receiver operating characteristic curves for various time series datasets indicate that the MSV registration improves the activation detection capability when compared to results obtained from Statistical Parametric Mapping (SPM). The effect of temporal median filtering of motion parameters on activation detection performance was also investigated.
Yeo
Desmond T B
DT
Department of Radiology, University of Michigan Medical School, MI 48109, USA. tbyeo@umich.edu
Bhagalia
Roshni R
RR
Kim
Boklye
B
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods*; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique