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Estimation of the Rigid-Body Motion from Three-Dimensional Images Using a Generalized Center-of-Mass Points Approach
B Feng1, P P Bruyant, P H Pretorius
1B. Feng, P. P. Bruyant, P. H. Pretorius, R. D. Beach, H. C. Gifford, J. Dey, and M. A. King are with the Department of Radiology, University of Massachusetts Medical School, Worcester, MA 01655. M. Gennert is with the Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA.
IEEE Transactions on Nuclear Science
|December 17, 2008
Summary
This study introduces a new method using generalized center-of-mass points to estimate and correct rigid-body motion in SPECT and PET imaging. The technique effectively reduces motion artifacts in 3D tomographic images, improving image quality.
Area of Science:
- Medical Imaging
- Nuclear Medicine
- Image Processing
Background:
- Rigid-body motion during SPECT and PET scans introduces artifacts, degrading image quality and diagnostic accuracy.
- Accurate motion estimation is crucial for effective compensation in 3D tomographic imaging.
Purpose of the Study:
- To develop and evaluate an analytical method for estimating rigid-body motion in 3D SPECT and PET images.
- To assess the effectiveness of this method in reducing motion artifacts through simulations and phantom studies.
Main Methods:
- Utilized mathematically defined generalized center-of-mass points, requiring no image segmentation.
- Generalized the center-of-mass formula to identify optimal points for motion estimation.
- Applied estimated motion for image summation and iterative reconstruction correction.
- Compared the generalized center-of-mass method with the principle-axes method.
Main Results:
- The generalized center-of-mass method effectively reduced visual and quantitative motion artifacts in SPECT and PET imaging.
- Simulations with MCAT and anthropomorphic phantoms demonstrated the method's ability to compensate for motion.
- The method showed comparable or improved motion estimation accuracy against the principle-axes method in phantom studies.
Conclusions:
- The developed analytical method provides a robust approach for estimating and correcting rigid-body motion in 3D SPECT and PET.
- This technique holds promise for applications such as correcting respiratory motion in gated SPECT and PET imaging.
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