Motion detection and correction for MR imaging using a structured light optical motion tracking system (SLOMO).

PURPOSE: To develop a markerless structured light system (SLOMO) for both rigid (brain) and non-rigid (liver) motion correction in MR imaging.

METHODS

The Structured Light Optical MOtion Tracking System (SLOMO) consisted of an MR- compatible camera and a parallel-line projector. The accuracy and precision of the SLOMO were evaluated by phantom experiments. The SLOMO was validated on five volunteers via brain imaging, in which the rigid motion of the head was extracted by registering the SLOMO-measured 3D face point clouds and used to correct the acquired k-space data. Additionally, the capability of SLOMO in non-rigid motion detection was evaluated in liver imaging of three volunteers. During each scan, the respiratory curve was extracted from 3D neck surface changes and then used to divide the acquired data into four respiratory bins; data of each bin was finally reconstructed into images, respectively. For comparison, bellow-based binning and sequential- binning served as references.

RESULTS

The tracking accuracy (evaluated via phantom image registration) and precision (evaluated via static phantom tracking) of the SLOMO were 0.38 mm/0.25°and 0.0048 mm/0.0019°, respectively. In brain imaging, SLOMO-corrected images had significantly higher image quality scores than uncorrected images (P < 0.001). In liver imaging, the correlation coefficient (r) between the respiratory curves extracted from the SLOMO and the bellow was 0.92 ± 0.04; images reconstructed from the bellow- bins and the SLOMO-bins showed comparable image quality (P = 0.38), while both were significantly higher than those from sequential-bins.

CONCLUSION

The proposed SLOMO demonstrated its capability in rigid and non-rigid motion detection and correction for MR brain and liver imaging.