Investigative Magnetic Resonance Imaging

Korean Society of Magnetic Resonance in Medicine (대한자기공명의과학회)
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Head Motion Detection and Alarm System during MRI scanning

MRI 영상획득 중의 피험자 움직임 감지 및 알림 시스템

  • Pae, Chong-Won (Brain Korea 21 Project for Medical Science, Yonsei University) ;
  • Park, Hae-Jeong (Brain Korea 21 Project for Medical Science, Yonsei University) ;
  • Kim, Dae-Jin (Department of Radiology and Division of Nuclear Medicine, College of Medicine, Yonsei University)
  • 배종원 (연세대학교 의과대학 의과학과) ;
  • 박해정 (연세대학교 의과대학 의과학과) ;
  • 김대진 (연세대학교 의과대학 핵의학과 및 영상의학교실)
  • Received : 2011.12.13
  • Accepted : 2012.04.17
  • Published : 2012.04.30
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Abstract

Purpose : During brain MRI scanning, subject's head motion can adversely affect MRI images. To minimize MR image distortion by head movement, we developed an optical tracking system to detect the 3-D movement of subjects. Materials and Methods: The system consisted of 2 CCD cameras, two infrared illuminators, reflective sphere-type markers, and frame grabber with desktop PC. Using calibration which is the procedure to calculate intrinsic/extrinsic parameters of each camera and triangulation, the system was desiged to detect 3-D coordinates of subject's head movement. We evaluated the accuracy of 3-D position of reflective markers on both test board and the real MRI scans. Results: The stereo system computed the 3-D position of markers accurately for the test board and for the subject with glasses with attached optical reflective marker, required to make regular head motion during MRI scanning. This head motion tracking didn't affect the resulting MR images even in the environment varying magnetic gradient and several RF pulses. Conclusion: This system has an advantage to detect subject's head motion in real-time. Using the developed system, MRI operator is able to determine whether he/she should stop or intervene in MRI acquisition to prevent more image distortions.

목적 : 자기공명영상(MRI) 획득시 피험자의 머리 움직임은 영상의 품질에 영향을 줄 수 있다. 영상 왜곡의 발생 원인이 되는 피험자의 움직임을 감지하기 위한 3차원 광학 추적 시스템을 제작하였다. 대상 및 방법 : 시스템은 두 대의 CCD 카메라 및 적외선 조명, 구형 반사 마커, 프레임 그래버(frame grabber)와 데스크탑 컴퓨터로 구성되었다. 두 대의 카메라를 이용하여 마커의 움직임을 관측하는 스테레오 비전 시스템을 제작하고, 카메라의 내부/외부 매개변수를 측정하는 캘리브레이션(calibration)과 측정된 매개변수를 이용하여 3차원 움직임 정보를 계산하는 삼각측량(triangulation)기법을 적용하였다. 캘리브레이션 보드와 피험자용 안경을 제작하여 움직임 추적의 정확도와 실제 MRI 영상 촬영 동안의 움직임 검출의 유효성을 평가하였다. 결과 : 반사 마커가 부착된 안경을 쓴 피험자들이 MRI 영상 촬영 동안 머리를 규칙적으로 움직였을 때, 시스템은 MRI의 고자장 환경 내에서도 영상에 영향을 주지 않고 피험자들의 움직임을 잘 감지했다. 결론 : 제작한 스테레오 비전 시스템은피험자의 머리 움직임을 잘 감지하였고, 실시간 알림 기능을 통해 피험자의 움직임을 중지할 수 있도록 알려줌으로써 MRI 영상에 영향을 주는 것을 최소화할 수 있다.

Keywords

References

  1. 대한자기공명의과학회, 자기공명영상학, 일조각, 2008
  2. Allen ED, Bryd SE, Darling CF, et al. The clinical and radiological evaluation of primary brain neoplasm in children, Part II: radiological evaluation. J Natl Med Assoc 1993;85:546-553
  3. Deck MD, Hanschke C, Lee BC, et al. Computed tomography versus magnetic resonance imaging of the brain. Clin Imaging 1989;13:2-15
  4. Bandettini PA, Wong EC, Hinks RS, Tikofsky RS, Hyde JS. Time course EPI of human brain-function during task activation. Magn Reson Med 1992;25:390-397
  5. Ogawa S, Tank DW, Menon R, et al. Intrinsic signal changes accompanying sensory stimulation-functional brain mapping with magnetic-resonance-imaging, Proc. Natl Acad Sci USA, 1992;89:5951-5955
  6. Na SM, Park HJ, Chang Y. Low Frequency fluctuation component analysis in active stimulation fMRI paradigm. J Korean Soc Magn Reson Med 2010;14:115-120
  7. G.Sudhir, S.Banerjee and A.Zisserman. Finding point correspondence in motion sequence preserving affine structure, Computer Vision and Image Understanding 1997;68:237-246
  8. V.A. Christpoulos, P. DeMuynck and J. Cornelis. Contour simplification for segmented stillimage and video coding: algorithms and experimental results, Signal Processing : Image Communication, 1999;14:335-357
  9. H Chen, D Ye, et al. A technique for binocular stereo vision system calibration by the nonlinear optimization and calibration points with accurate coordinates, Institute fo Physics Publishing Journal of Physics: Conference Series 48, 2006
  10. Tsai RY. A versatile camera calibration technique for high accuracy 3D machine vision metrology using offtheshelf TV cameras and lenses, IEEE Jouenal of Robotics and Automation RA-3(4):323-344, 1987
  11. Zhengyou Zhang. A flexible new technique for camera calibration, Technical report, Microsoft Research, 2002
  12. B.Jean Yves, P.Pietro. Camera calibration from points and ones in dual-space geometry, European conference on computer vision, 1998
  13. R.I.Hartley and A. Zisserman. Multiple view geometry in computer vision. Cambridge University Press 2000:237-361
  14. O. Faugeras. Three-dimensional computer vision: a geometric viewpoint. MIT Press, 1993
  15. Don Koks. A roundabout route to geometric algebra, explorations in Mathematical Physics, Springer Science+ Business Media, LLC. 2006;144-183
  16. Chaurasia BD, Mathur BB (1976). Eyedness. Acta Anat (Basel) 96(2):301-305
  17. SPM, Statistical Parametric Mapping, http://www.fil.ion.ucl.ac.uk/spm/
  18. Qin L, van Gelderen P, Derbyshire JA, et al. Prospective headmovement correction for high-resolution MRI using an in-bore optical tracking system, Magn Resonin Med 2009;62:924-934
  19. Forman C, Aksoy M, Hornegger J, Bammer R. Self-encoded marker for optical prospective head motion correcetion in MRI. Med Image Anal 2011;15:708-719
  20. M.Zaitsev, C.Dold, G. Sakas, et al. Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system, Neuroimage 2006;31:1038-1050
  21. http://www.mrc-systems.de/englisch/products/mrcamera.html
  22. S.J. Maybank and O.D. Faugeras. A theory of selfcalibration of a moving camera. The international Journal of Computer Vision 1992;8:123-152
  23. Q.-T. Luong and O.Faugeras, Self-calibration of a moving camera from point correspondences and fundamental matrices The International Journal of Computer Vision 1997;22:261-289
  24. R.I. Hartley. An algorithm for self calibration from several views, In Proc. IEEE Conference on Computer Vision and Pattern Recognition, 908-912, Seattle, WA, June 1994
  25. S. Bounoux. From projective to euclidean space under any practical situation, a criticism of self-calibration, In Proc. 6th International Conference on Computer Vision, 1998;790-796