Abstract
In the context of retinal microsurgery, visual tracking of instruments is a key component of robotics assistance. The difficulty of the task and major reason why most existing strategies fail on in-vivo image sequences lies in the fact that complex and severe changes in instrument appearance are challenging to model. This paper introduces a novel approach, that is both data-driven and complementary to existing tracking techniques. In particular, we show how to learn and integrate an accurate detector with a simple gradient-based tracker within a robust pipeline which runs at framerate. In addition, we present a fully annotated dataset of retinal instruments in in-vivo surgeries, which we use to quantitatively validate our approach. We also demonstrate an application of our method in a laparascopy image sequence.
Supplementary Material: Here is the link to a webpage that contains the dataset associated with this paper (the associated videos will uploaded to this page as well): https://sites.google.com/site/sznitr/research/datadrivendetection . A brief description of the paper is also provided on the website.
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Uneri, A., Balicki, M., Handa, J., Gehlbach, P., Taylor, R., Iordachita, I.: New steady-hand eye robot with micro-force sensing for vitreoretinal surgery. In: 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 814–819 (September 2010)
Balicki, M., Han, J.H., Iordachita, I., Gehlbach, P., Handa, J., Taylor, R., Kang, J.: Single Fiber Optical Coherence Tomography Microsurgical Instruments for Computer and Robot-Assisted Retinal Surgery. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part I. LNCS, vol. 5761, pp. 108–115. Springer, Heidelberg (2009)
Pezzementi, Z., Voros, S., Hager, G.D.: Articulated object tracking by rendering consistent appearance parts. In: IEEE International Conference on Robotics and Automation, pp. 3940–3947 (May 2009)
Sznitman, R., Basu, A., Richa, R., Handa, J., Gehlbach, P., Taylor, R., Jedynak, B., Hager, G.: Unified Detection and Tracking in Retinal Microsurgery. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol. 6891, pp. 1–8. Springer, Heidelberg (2011)
Burschka, D., Corso, J.J., Dewan, M., Lau, W., Li, M., Lin, H., Marayong, P., Ramey, N., Hager, G.D., Hoffman, B., Larkin, D., Hasser, C.: Navigating inner space: 3-d assistance for minimally invasive surgery. Robotics and Autonomous Systems 52, 5–26 (2005)
Richa, R., Balicki, M., Meisner, E., Sznitman, R., Taylor, R., Hager, G.: Visual Tracking of Surgical Tools for Proximity Detection in Retinal Surgery. In: Taylor, R.H., Yang, G.-Z. (eds.) IPCAI 2011. LNCS, vol. 6689, pp. 55–66. Springer, Heidelberg (2011)
Voros, S., Long, J.A., Cinquin, P.: Automatic detection of instruments in laparoscopic images: A first step towards high-level command of robotic endoscopic holders. International Journal of Robotic Research 26(11-12), 1173–1190 (2007)
Ali, K., Fleuret, F., Hasler, D., Fua, P.: A real-time deformable detector. Transactions on Pattern Analysis and Machine Intelligence 34(2), 225–239 (2011)
Benhimane, S., Malis, E.: Homography-based 2D Visual Tracking and Servoing. International Journal of Robotics Research 26(7), 661–676 (2007)
Pickering, M., Muhit, A., Scarvell, J., Smith, P.: A new multi-modal similarity measure for fast gradient-based 2d-3d image registration. In: Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, pp. 5821–5824 (September 2009)
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Sznitman, R., Ali, K., Richa, R., Taylor, R.H., Hager, G.D., Fua, P. (2012). Data-Driven Visual Tracking in Retinal Microsurgery. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_70
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DOI: https://doi.org/10.1007/978-3-642-33418-4_70
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