Carotid artery imaging is hampered by motion artefacts, including those caused by occasional swallowing motion. In this work, we extend previous work on intelligent reacquisition to estimate and replace motion-corrupted data. ‘Bad’ phase-encode lines were synthesized from surrounding ‘good’ lines using parallel imaging techniques. Estimation and replacement of corrupted data reduced background ghosting levels in comparison to the previous reacquisition approach. A small number of reacquisitions was maintained to ensure good quality data at the centre of k-space because these are essential for image quality and for calibration of the parallel imaging-based estimation.