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Vision-Based Assistance for Ophthalmic Micro-Surgery

  • Maneesh Dewan
  • Panadda Marayong
  • Allison M. Okamura
  • Gregory D. Hager
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3217)

Abstract

This paper details the development and preliminary testing of a system for 6-DOF human-machine cooperative motion using vision-based virtual fixtures for applications in retinal micro-surgery. The system makes use of a calibrated stereo imaging system to track surfaces in the environment, and simultaneously tracks a tool held by the JHU Steady-Hand Robot. As the robot is guided using force inputs from the user, a relative error between the estimated surface and the tool position is established. This error is used to generate an anisotropic stiffness matrix that in turn guides the user along the surface in both position and orientation. Preliminary results show the effectiveness of the system in guiding a user along the surface and performing different sub-tasks such as tool alignment and targeting within the resolution of the visual system.The accuracy of surface reconstruction and tool tracking obtained from stereo imaging was validated through comparison with measurements made by an infrared optical position tracking system.

Keywords

Prefer Direction Surface Reconstruction Retinal Vein Occlusion Central Retinal Vein Occlusion Branch Retinal Vein Occlusion 
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

  1. 1.
    Bettini, A., Marayong, P., Lang, S., Okamura, A.M., Hager, G.D.: Vision assisted control for manipulation using virtual fixtures. In: IEEE ITRA (to appear)Google Scholar
  2. 2.
    Bressler, N., Bressler, S., Fine, S.: Age-related macular degeneration. Survey of Ophthalmology 32(6), 375–413 (1988)CrossRefGoogle Scholar
  3. 3.
    Corso, J., Chhugani, J., Okamura, A.: Interactive haptic rendering of deformable surfaces based on the medial axis transform. Eurohaptics, 92–98 (2002)Google Scholar
  4. 4.
    Hager, G.D.: Vision-based motion constraints. In: IEEE/RSJ IROS, Workshop on Visual Servoing (2002), http://www.cs.jhu.edu/CIRL/new/publications.html
  5. 5.
    Hager, G.D., Toyama, K.: The XVision system: A general purpose substrate for real-time vision applications. CVIU 69(1), 23–27 (1998)Google Scholar
  6. 6.
    Kragic, D., Hager, G.: Task modeling and specification for modular sensory based human-machine cooperative systems. IEEE/RSJ IROS 4, 3192–3197 (2003)Google Scholar
  7. 7.
    Kumar, R., Hager, G.D., Jensen, P., Taylor, R.H.: An augmentation system for fine manipulation. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 956–965. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  8. 8.
    Lai, F., Howe, R.D.: Evaluating control modes for constrained robotic surgery. In: IEEE ICRA, pp. 603–609 (2000)Google Scholar
  9. 9.
    Lau, W., Ramey, N.A., Corso, J.J., Thakor, N., Hager, G.D.: Stereo-based endoscopic tracking of cardiac surface deformation. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3217, pp. 494–501. Springer, Heidelberg (2004) (to appear)CrossRefGoogle Scholar
  10. 10.
    Group, M.P.S.: Argon laser photocoagulation for neovascular maculopathy. 5 yrs results from randomized clinical trial. Arch Ophthalmol 109, 1109–1114 (1991)Google Scholar
  11. 11.
    Marayong, P., Li, M., Okamura, A., Hager, G.: Spatial motion constraints: Theory and demonstrations for robot guidance using virtual fixtures. In: IEEE ICRA, pp. 1954–1959 (2003)Google Scholar
  12. 12.
    Payandeh, S., Stanisic, Z.: On application of virtual fixtures as an aid for telemanipulation and training. In: Symposium on Haptic Interfaces For Virtual Environments and Teleoperator Systems, pp. 18–23 (2002)Google Scholar
  13. 13.
    Ramey, N.: Stereo-based direct surface tracking with deformable parametric models. Master’s thesis, Dept. of Biomedical Engineering, Johns Hopkins University (2003) Google Scholar
  14. 14.
    Rosenberg, L.: Virtual fixtures: perceptual tools for telerobotic manipulation. In: IEEE Virtual Reality International Sympsoium, pp. 76–82 (1993)Google Scholar
  15. 15.
    Scott, I.: Vitreoretinal surgery for complications of branch retinal vein occlusion. Curr. Opin. Ophthalmol. 13, 161–166 (2002)CrossRefGoogle Scholar
  16. 16.
    Taylor, R., et al.: Steady-hand robotic system for microsurgical augmentation. IJRR 18(12), 1201–1210 (1999)Google Scholar
  17. 17.
    Weiss, J.N.: Injection of tissue plasminogen activator into a branch retinal vein in eyes with central retinal vein occlusion. Ophthalmology 108(12), 2249–2257 (2001)CrossRefGoogle Scholar
  18. 18.
    Wren, C.R., Azarbayejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of human body. IEEE PAMI 19(7), 780–785 (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Maneesh Dewan
    • 1
  • Panadda Marayong
    • 2
  • Allison M. Okamura
    • 2
  • Gregory D. Hager
    • 1
  1. 1.Department of Computer ScienceJohns Hopkins UniversityBaltimore
  2. 2.Department of Mechanical EngineeringJohns Hopkins UniversityBaltimore

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