Motion Tracking in Narrow Spaces: A Structured Light Approach

We present a novel tracking system for patient head motion inside 3D medical scanners. Currently, the system is targeted at the Siemens High Resolution Research Tomograph (HRRT) PET scanner. Partial face surfaces are reconstructed using a miniaturized structured light system. The reconstructed 3D point clouds are matched to a reference surface using a robust iterative closest point algorithm. A main challenge is the narrow geometry requiring a compact structured light system and an oblique angle of observation. The system is validated using a mannequin head mounted on a rotary stage. We compare the system to a standard optical motion tracker based on a rigid tracking tool. Our system achieves an angular RMSE of 0.11 degrees demonstrating its relevance for motion compensated 3D scan image reconstructions as well as its competitiveness against the standard optical system with an RMSE of 0.08 degrees. Finally, we demonstrate qualitative result on real face motion estimation.

[1]  N Raghunath,et al.  Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization , 2009, Physics in medicine and biology.

[2]  Munther A. Gdeisat,et al.  Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path. , 2002, Applied optics.

[3]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[4]  Rasmus Larsen,et al.  Markov Random Field Surface Reconstruction , 2010, IEEE Transactions on Visualization and Computer Graphics.

[5]  Wei Lu,et al.  Reconstruction of 4D-CT data sets acquired during free breathing for the analysis of respiratory motion , 2006, SPIE Medical Imaging.

[6]  Rasmus Larsen,et al.  Structured light 3D tracking system for measuring motions in PET brain imaging , 2010, Medical Imaging.

[7]  T. Zeffiro,et al.  Head movement in normal subjects during simulated PET brain imaging with and without head restraint. , 1994, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[8]  M. Sibomana,et al.  Spatial resolution of the HRRT PET scanner using 3D-OSEM PSF reconstruction , 2009, 2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC).

[9]  Mikkel B. Stegmann,et al.  Motion-Compensation of Cardiac Perfusion MRI Using a Statistical Texture Ensemble , 2003, FIMH.

[10]  Hervé Delingette,et al.  Functional Imaging and Modeling of the Heart, 5th International Conference, FIMH 2009, Nice, France, June 3-5, 2009. Proceedings , 2009, Functional Imaging and Modeling of the Heart.

[11]  C. J. Thompson,et al.  Motion correction of PET images using multiple acquisition frames , 1997, IEEE Transactions on Medical Imaging.

[12]  Dean F. Wong,et al.  Accurate Event-Driven Motion Compensation in High-Resolution PET Incorporating Scattered and Random Events , 2008, IEEE Transactions on Medical Imaging.

[13]  H. Herzog,et al.  Motion correction in PET brain studies , 2005, The Fourth International Workshop on Multidimensional Systems, 2005. NDS 2005..

[14]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Michael M. Kazhdan,et al.  Poisson surface reconstruction , 2006, SGP '06.

[16]  B. Lopresti,et al.  Implementation and performance of an optical motion tracking system for high resolution brain PET imaging , 1998, 1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255).

[17]  A. Mijiritskii,et al.  Surface reconstruction of Fe3O4(100) , 2000 .

[18]  H. Iida,et al.  Sinogram-based motion correction of PET images using optical motion tracking system and list-mode data acquisition , 2004, IEEE Transactions on Nuclear Science.

[19]  Fu-Pen Chiang,et al.  Color-encoded digital fringe projection technique for high-speed three-dimensional surface contouring , 1999 .

[20]  Marc Levoy,et al.  Efficient variants of the ICP algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.