Abstract
This paper suggests an ultrasound guided needle insertion instrument which can track target motion in real-time. Under traditional ultrasound guided needle insertion therapies, surgeons have had much burden to find out the precise targeting position, particularly when the organ is moving due to the respiration or heartbeat. We developed a new needle insertion instrument which can track moving target based on visual servo control. In addition, this paper proposed a tumor specific active contour model which can conduct a fast and robust segmentation for tumor, and utilized Hough transform for needle recognition. In the experiment, the proposed system could track a moving phantom successfully at speed of 3 frames/sec processing.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
M. Kudo: Percutaneous needle placement into hepatic tumors under ultrasound vascular image guidance. Journal of clinical surgery, Vol. 55. (2000) 1551–1555
M. Hiroda, T. Becpoo, S. Shimada, M. ogawa: Percutaneous ultrasound-guided microwave coagulation therapy for hepatic neoplasms. Journal of clinical surgery, Vol. 55. (2000) 1557–1560
M.H. Loser, N. Navab: A New Robotic System for visually Controlled Percutaneous Interventions under CT Fluoroscopy. MICCAI 2000, Lecture Notes in Computer Science, Vol. 1935. Springer-Verlag (2000) 887–896
A. Patriciu, D. Stoianovici, L.L. Whitcomb, T Jarrett, D. Mazilu, A. Stanimir, I. Iordachita, J. Anderson, R. Taylor, L.R. Kavoussi: Motion-Based Robotic Instrument Targeting Under C-Arm Fluoroscopy. MICCAI 2000, Lecture Notes in Computer Science, Vol. 1935. Springer-Verlag (2000) 988–998
T. Dohi, ”Medical Imaging for Computer Aided Surgery: IEICE Trans. Inf. and Syst., Vol. J83-D-II. (2000) 27–33
Y. Nakamura, K. Kishi, H. Kawakami: Heartbeat Sysncronization for Robotic Cardiac Surgery. ICRA2001, IEEE International Conference on Robotics and Automation (2001) 2014–2019
S.E. Salcudean, G. Bell, S. Bachmann,et et al.: Robot-assisted diagnostic ultrasound-design and feasibility experiments. Proc. MICCAI 1999, Lecture Notes in Computer Science, Vol. 1679 (1999) 1062–1071
R. H. Taylor, J. Funda, B. Eldridge, D. Larose, M. Talamini, L. Kavoussi, J. Anderson: A telerobotic assistant for laparoscopic surgery. in Proc. Int. Conf. On Advanced Robots (1995) 33–36
G.Q. Wei, K. Arbter, G. Hirzinger: Real-Time Visual Servoing for Laparoscopic Surgery. IEEE Eng. in Med. and Biol, Vol. 16 (1997) 40–45
G.D. Hager, S. Hutchinson and P. Corke: A Tutorial on Visual Servo Control. IEEE Transactions on Robotics and Automation, Vol. 12 (1996) 651–670
R. Kelly, R. Carelli, O. Nasis, B. Kuchen, F. Reyes:Stable Visual Servoing of Camera-in-Hand Robotic Systems. IEEE Trans. Mechatoronics, Vol. 5 (2000) 39–48
M. Kass, A. Witkin, and D. Terzopoulos: Snakes:Active Contour Models. Proceeding of First International Conference on Computer Vision (1987) 259–256
M. Mignotte, J. Meunier: A multiscale optimization approach for the dynamic contour-based boundary detection issue. Computerized Medical Imaging and Graphics, Vol 25. (2001) 265–275
J.S. Hong, T. Kaneko, R. Sekiguchi and K.H. Park: Automatic Liver Tumor Detection from CT. IEICE Trans. Inf. and Syst., Vol. E84-D. (2001) 741–748
C. Choi, S.M. Lee, N.C. Kim, and H. Son: Image segmentation and coding using edge tracing. J. KITE, Vol. 26. (1989) 105–112
E. J. Delp and C.H. Chu: Detecting edge segments. IEEE Trans. On Sys. Man and Cybern., Vol SMC-15 (1985) 144–152
Hough P.V.C.:A Method and Means for Recognizing Complex Patterns. U.S. Patent No. 3069654 (1962)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hong, JS., Dohi, T., Hasizume, M., Konishi, K., Hata, N. (2002). A Motion Adaptable Needle Placement Instrument Based on Tumor Specific Ultrasonic Image Segmentation. In: Dohi, T., Kikinis, R. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. MICCAI 2002. Lecture Notes in Computer Science, vol 2488. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45786-0_16
Download citation
DOI: https://doi.org/10.1007/3-540-45786-0_16
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44224-0
Online ISBN: 978-3-540-45786-2
eBook Packages: Springer Book Archive