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Published on: February 12, 2013
Motion detection and correction for MR imaging using a structured light optical motion tracking system (SLOMO)
Chunyao Wang1, Tianqi Huang2, Yuze Li1
1Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China.
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.
Insights
A new markerless structured light system (SLOMO) effectively corrects rigid and non-rigid motion in MRI scans. This technology improves image quality for both brain and liver imaging, offering a significant advancement in motion artifact reduction.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Image Processing
Background:
- Motion artifacts are a significant challenge in Magnetic Resonance Imaging (MRI), degrading image quality and potentially affecting diagnostic accuracy.
- Existing methods for motion correction often rely on external sensors or are limited to specific types of motion (rigid or non-rigid).
- There is a need for a versatile, markerless system capable of addressing both rigid and non-rigid motion in various anatomical regions.
Purpose of the Study:
- To develop and evaluate a novel markerless structured light system, termed SLOMO (Structured Light Optical MOtion Tracking System).
- To assess SLOMO's capability for correcting rigid motion in brain MRI.
- To evaluate SLOMO's effectiveness in detecting and correcting non-rigid motion during liver MRI.
Main Methods:
- The SLOMO system utilizes an MR-compatible camera and a parallel-line projector to capture 3D surface data.
- Phantom experiments were conducted to determine the system's accuracy and precision.
- Clinical validation involved acquiring brain MRI data from five volunteers for rigid motion correction and liver MRI data from three volunteers for non-rigid motion detection, comparing results with traditional bellow-based and sequential binning methods.
Main Results:
- SLOMO demonstrated high tracking accuracy (0.38 mm/0.25°) and precision (0.0048 mm/0.0019°) in phantom studies.
- Brain MRI images corrected using SLOMO showed significantly improved quality compared to uncorrected images (P < 0.001).
- In liver imaging, SLOMO-derived respiratory curves strongly correlated with bellow measurements (r = 0.92 ± 0.04), and reconstructed images exhibited comparable quality to bellow-based binning, outperforming sequential binning.
Conclusions:
- The developed SLOMO system is effective for markerless detection and correction of both rigid and non-rigid motion in MRI.
- SLOMO significantly enhances image quality in brain imaging by correcting for head motion.
- The system shows promise for real-time respiratory motion management in liver MRI, providing results comparable to established methods.
