Servo navigators: Linear regression and feedback control for rigid‐body motion correction

Abstract

AbstractPurposeNavigator‐based correction of rigid‐body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing.MethodsA short orbital navigator (2.3 ms) is inserted in a three‐dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex‐valued model built either from three reference navigators or in a reference‐less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run‐time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion‐corrected imaging in vivo.ResultsThe proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0. It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single‐digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality.ConclusionThe combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run‐time computation, and minimal demand for reference data.