Download or read book Comprehensive Head Motion Correction For Functional Magnetic Resonance Imaging written by Zahra Faraji-Dana and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Head motion artifacts are major confounds that limit use of functional magnetic resonance imaging (fMRI) in neuroscience research and clinical settings. Prospective motion correction is a promising candidate solution for head motion in fMRI that ideally allows the image plane to remain fixed with respect to the moving head (i.e., in the moving reference frame). Prospective motion correction has been shown to correct successfully for rigid body movement artifacts, but residual geometric distortion due to dynamic magnetic field nonuniformities and dynamic changes in receiver coil sensitivity profiles in the moving reference frame still remain a problem. This thesis focuses on three objectives. First, I investigated and corrected for the influence of respiratory effects on the performance of dynamic geometric correction using Phase Labeling for Additional Coordinate Encoding (PLACE). It was demonstrated that PLACE combined with the dynamic off-resonance in k-space (DORK) method, and temporal averaging substantially improved fMRI data quality in comparison to the results obtained by standard processing and static geometric distortion correction. Second, I verified that appreciable signal artifacts occur due to coil sensitivity changes in fMRI maps in presence of overt head motion with prospective motion correction using Prospective Acquisition CorrEction (PACE) technique [1]. Sensitivity map compensations were shown to suppress these artifacts and provide improved fMRI results Third, I studied signal artifacts resulted from the head motion between the coil sensitivity map measurement (i.e., the calibration step) and data acquisition for fMRI with parallel-imaging reconstruction methods using two parallel imaging schemes: sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA) with acceleration factors 2 and 4. Coil sensitivity map compensations were shown to improve fMRI results obtained with PACE in the presence of overt head motion compared to those obtained with no overt head motion. Overall, prospective motion correction, integrated dynamic geometric distortion correction, and coil sensitivity map correction present an appealing compound approach for suppressing rigid and non-rigid motion artifacts during fMRI. This thesis has developed robust and comprehensive head motion correction strategies that ultimately will expand the patient populations for which fMRI can be performed robustly.