Self-navigated motion correction in multi-contrast intracranial vascular imaging using 3D radial trajectory

Motivation: iSNAP is a time-efficient multi-contrast intracranial vascular imaging sequence that uses 3D radial acquisition trajectory. Motion, commonly occurs in cerebrovascular patients, decreases quality of iSNAP images. Goal(s): To develop a motion correction approach for iSNAP sequence. Approach: Self-navigated motion correction, in which a series of high temporal-resoluaiton images were reconstructed for motion estimation, was implemented by taking advantage of radial trajectory. Performance of the approach was assessed with simulation and in-vivo experiments. Results: The proposed approach allows detection and correction of large abrupt rotations and translations in steady states. Impact: The proposed retrospective motion correction approach improves image quality of iSNAP, and enhances its clinical value.