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JRM Vol.29 No.2 pp. 434-446
doi: 10.20965/jrm.2017.p0434
(2017)

Paper:

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Servoing Performance Enhancement via a Respiratory Organ Motion Prediction Model for a Non-Invasive Ultrasound Theragnostic System

Tatsuya Fujii*1, Norihiro Koizumi*2, Atsushi Kayasuga*1, Dongjun Lee*1, Hiroyuki Tsukihara*1, Hiroyuki Fukuda*3, Kiyoshi Yoshinaka*4, Takashi Azuma*1, Hideyo Miyazaki*1, Naohiko Sugita*1, Kazushi Numata*3, Yukio Homma*1, Yoichiro Matsumoto*1, and Mamoru Mitsuishi*1

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

*2The University of Electro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

*3Yokohama City University
4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan

*4National Institute of Advanced Industrial Science and Technology
1-2-1 Namiki, Tsukuba, Ibaraki 305-8564, Japan

Received:
January 28, 2016
Accepted:
January 18, 2017
Published:
April 20, 2017
Creative Commons License
Keywords:
HIFU, motion tracking, theragnostics, ultrasound robot, physiological motion compensation
Abstract
High intensity focused ultrasound (HIFU) is potentially useful for treating stones and/or tumors. With respect to HIFU therapy, it is difficult to focus HIFU on the focal lesion due to respiratory organ motion, and this increases the risk of damaging the surrounding healthy tissues around the target focal lesion. Thus, this study proposes a method to cope with the fore-mentioned problem involving tracking and following the respiratory organ motion via a visual feedback and a prediction model for respiratory organ motion to realize highly accurate servoing performance for focal lesions. The prediction model is continuously updated based on the latest organ motion data. The results indicate that respiratory kidney motion of two healthy subjects is successfully tracked and followed with an accuracy of 0.88 mm by the proposed method and the constructed system.
Proposed method for tracking and following respiratory organ motion

Proposed method for tracking and following respiratory organ motion

Cite this article as:
T. Fujii, N. Koizumi, A. Kayasuga, D. Lee, H. Tsukihara, H. Fukuda, K. Yoshinaka, T. Azuma, H. Miyazaki, N. Sugita, K. Numata, Y. Homma, Y. Matsumoto, and M. Mitsuishi, “Servoing Performance Enhancement via a Respiratory Organ Motion Prediction Model for a Non-Invasive Ultrasound Theragnostic System,” J. Robot. Mechatron., Vol.29 No.2, pp. 434-446, 2017.
Data files:
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