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JRM Vol.25 No.6 pp. 1088-1096
doi: 10.20965/jrm.2013.p1088
(2013)

Paper:

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Construction Methodology for NIUTS – Bed Servoing System for Body Targets –

Norihiro Koizumi*, Joonho Seo*, Takakazu Funamoto*,
Yutaro Itagaki*, Akira Nomiya**, Akira Ishikawa**,
Hiroyuki Tsukihara*,**, Kiyoshi Yoshinaka***, Naohiko Sugita*,
Yukio Homma**, Yoichiro Matsumoto*, and Mamoru Mitsuishi*

*Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

**Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan

***National Institute of Advanced Industrial Science and Technology (AIST), 1-2-1 Namiki, Tsukuba, Ibaraki 305-8564, Japan

Received:
October 22, 2012
Accepted:
October 21, 2013
Published:
December 20, 2013
Creative Commons License
Keywords:
non-invasive ultrasound theragnostic system (NIUTS), technologizing and digitalization of medical professional skills (TDMPS), high intensity focused ultrasound (HIFU), theragnostics, ultrasound diagnostic and therapeutic robot
Abstract

Unwanted motion is a serious problem in enhancing servoing performance in an affected area, which incorporates stones/tumours in non-invasive ultrasound theragnostic systems (NIUTS). To solve this problem, we proposed a new method for restricting the motion of the affected area ventrodorsally in the region of interest (ROI) in ultrasound imaging. To do so, we introduce a bed mechanism for NIUTS. It is confirmed that a human kidney could be tracked and followed appropriately using the proposedmethod and the newly constructed bed system.

Cite this article as:
N. Koizumi, J. Seo, T. Funamoto, <. Itagaki, A. Nomiya, A. Ishikawa, <. Tsukihara, K. Yoshinaka, N. Sugita, <. Homma, Y. Matsumoto, and M. Mitsuishi, “Construction Methodology for NIUTS – Bed Servoing System for Body Targets –,” J. Robot. Mechatron., Vol.25, No.6, pp. 1088-1096, 2013.
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References
  1. [1] J. E. Kennedy et al., “High-intensity focused ultrasound: surgery of the future?,” British J. of Radiology, Vol.76, pp. 590-599, 2003.
  2. [2] J. G. Lynn, R. L. Zwemer, A. J. Chick, and A. E. Miller, “A new method for the generation and use of focused ultrasound in experimental biology,” J. Gen. Physiol., Vol.26, pp. 179-193, 1942.
  3. [3] T. Ikeda, S. Yoshizawa, M. Tosaki, J. S. Allen, S. Takagi, N. Ohta, T. Kitamura, and Y. Matsumoto, “Cloud Cavitation Control for Lithotripsy Using High Intensity Focused Ultrasound,” Ultrasound Med. Biol., Vol.32, No.9, pp. 1383-1397, 2006.
  4. [4] F. Wu, Z. L. Wang, Z. Zhang et al., “Acute biological effects of high-intensity focused ultrasound on H22 liver tumours in vivo,” Chin. Ultrasound Med., Vol.13, No.3, 1997.
  5. [5] G. Tu, T. Y. Qiao, and S. He, “An experimental study on highintensity focused ultrasound in the treatment of VX-2 rabbit kidney tumours,” Chin. J. Urol., Vol.20, No.8, 1999.
  6. [6] F. Wu, W. Z. Chen, J. Bai, J. Z. Zou, Z. L. Wang, H. Zhu, and Z. B. Wang, “Pathological changes in malignant carcinoma treated with high-intensity focused ultrasound,” Ultrasound Med. Biol., Vol.27, No.8, pp. 1099-1106, 2001.
  7. [7] J. E. Kennedy et al., “High-intensity focused ultrasound for the treatment of liver tumours,” Ultrasound Med. Biol., Vol.42, pp. 931-935, 2004.
  8. [8] N. Koizumi, J. Seo, T. Funamoto, A. Nomiya, A. Ishikawa, K. Yoshinaka, N. Sugita, Y. Homma, Y. Matsumoto, and M. Mitsuishi, “Technologizing and Digitalizing Medical Professional Skills for a Non-Invasive Ultrasound Theragnostic System,” J. of Robotics and Mechatronics, Vol.24, No.2, pp. 379-388, 2012.
  9. [9] N. Koizumi, H. Tsukihara, S. Takamoto, H. Hashizume, and M. Mitsuishi, “Robot vision technology for technologizing and digitalization of medical diagnostic and therapeutic skills,” Int. J. of Automation Technology, Vol.3, No.5, pp. 541-550, 2009.
  10. [10] N. Koizumi, S. Warisawa, M. Nagoshi, H. Hashizume, and M. Mitsuishi, “Construction methodology for a remote ultrasound diagnostic system,” IEEE Trans. on Robotics, Vol.25, pp. 522-538, 2009.
  11. [11] N. Koizumi, T. Tsurumi, S. Warisawa, H. Hashizume, and M. Mitsuishi, “Probe positioning support utilizing shoulder model for ultrasound diagnosis,” Proc. of 2006 IEEE/RSJ Int. Conf. Intelligent Robotics and Systems, Vol.1, pp. 155-161, 2006.
  12. [12] N. Koizumi, J. Seo, Y. Suzuki, D. Lee, K. Ota, A. Nomiya, S. Yoshizawa, K. Yoshinaka, N. Sugita, H. Homma, Y. Matsumoto, and M. Mitsuishi, “A control framework for the non-invasive ultrasound theragnostic system,” Proc. of 2009 IEEE/RSJ Int. Conf. Intelligent Robotics and Systems, pp. 4511-4516, 2009.
  13. [13] N. Koizumi, J. Seo, D. Lee, T. Funamoto, A. Nomiya, K. Yoshinaka, N. Sugita, H. Homma, Y. Matsumoto, and M. Mitsuishi, “Robust kidney stone tracking for a non-Invasive ultrasound theragnostic system – Servoing performance and safety enhancement –,” Proc. of the 2011 IEEE Int. Conf. on Robotics and Automation, pp. 2443-2450, 2011.
  14. [14] M. Pernot et al., “3-D Real-Time Motion Correction in High-Intensity Focused Ultrasound Therapy,” Ultrasound in Med. Biol., Vol.30, No.9, pp. 1239-1249, 2004.
  15. [15] Y. Nakamura and H. Kishi, “Robotic Stabilization that Assists Cardiac Surgery on Beating Hearts,” Proc. of Medicine Meets Virtual Reality 2001, Ultrasound in Med. Biol., pp.355-361, 2001.
  16. [16] Y. Nakamura, H. Kishi, and H. Kawakami, “Heartbeat Synchronization for Robotic Cardiac Surgery,” Proc. of the 2001 IEEE Int. Conf. on Robotics and Automation, pp. 2014-2019, 2001.
  17. [17] A. Thankral, J.Wallace, D. Tomlin, N. Seth, and N. V. Thakor, “Surgical Motion Adaptive Robotic Technology (S.M.A.R.T): Tracking the Motion Out of Physiological Motion,” Proc. 2004 Int. Conf. Robotics and Automation, pp. 274-279, 2004.
  18. [18] R. Ginhoux, J. Gangloff, M. de Mathelin, L. Soler, M. M. A. Sanchez, and J. Marescaux, “Active filtering of physiological motion in robotized surgery using predictive control, model predictive control and an adaptive observer,” IEEE Trans. Robotics, Vol.21, pp. 67-79, 2005.
  19. [19] F. Yeung, F. Levinson, D. Fu, and K. J. Parker, “Feature-adaptive motion tracking of ultrasound image sequence using a deformable mesh,” IEEE Trans. Medical Imaging, Vol.17, pp. 945-956, 1998.
  20. [20] R. Mebarki, A. Krupa, and F. Chaumette, “Image moments-based ultrasound visual servoing,” Proc. 2008 Int. Conf. Robotics and Automation, Vol.1, pp. 113-119, 2008.
  21. [21] P. Abolmaesumi, S. E. Salcudean, W. H. Zhu, M. Sirouspour, and S. DiMaio, “Image-guided control of a robot for medical ultrasound,” IEEE Trans. Robotics and Automation, Vol.18, pp. 11-23, 2002.
  22. [22] A. Krupa, G. Fichtinger, and G. Hager, “Full motion tracking in ultrasound using image speckle information and visual servoing,” Proc. 2007 Int. Conf. Robotics and Automation, Vol.1, pp. 2458-2464, 2007.
  23. [23] F. Chaumette, “Image Moments: A general and useful set of features for visual servoing,” IEEE Trans. Robotics and Automation, Vol.20, pp. 713-723, 2004.
  24. [24] J. P. LaSalle, “The extent of asymptotic stability,” Proc. Nat. Acad. Sci., pp. 363-365, 1960.

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