An enhanced marker pattern that achieves improved accuracy in surgical tool tracking

References

• Allan M, Mcleod J, Wang CC, Rosenthal JC, Fu KX, Zeffiro T, Xia W, Zhanshi Z, Luo H, Zhang X, et al. 2021. Stereo correspondence and reconstruction of endoscopic data challenge. arXiv Preprint arXiv:210101133.
   Google Scholar
• Cartucho J, Tukra S, Li Y, S Elson D, Giannarou S. 2021. Visionblender: a tool to efficiently generate computer vision datasets for robotic surgery. Comput Methods Biomech Biomed Eng Imag Vis, 9(4):331–338.
   Google Scholar
• Facil JM, Ummenhofer B, Zhou H, Montesano L, Brox T, Civera J. 2019. Cam-convs: camera- aware multi-scale convolutions for single-view depth. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. p. 11826–11835.
   Google Scholar
• Gadwe A, Ren H. 2018. Real-time 6dof pose estimation of endoscopic instruments using printable markers. IEEE Sens J. 19(6):2338–2346. doi:https://doi.org/10.1109/JSEN.2018.2886418.
   Google Scholar
• Giannarou S, Ye M, Gras G, Leibrandt K, Marcus HJ, Yang GZ. 2016. Vision-based deformation recovery for intraoperative force estimation of tool–tissue interaction for neurosurgery. Int J Comput Assist Radiol Surg. 11(6):929–936. doi:https://doi.org/10.1007/s11548-016-1361-z.
   Google Scholar
• Hao R, Özgüner O, Çavuşoğlu MC. 2018. Vision-based surgical tool pose estimation for the da vinci® robotic surgical system. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. p. 1298–1305.
   Google Scholar
• Huang B, Tsai YY, Cartucho J, Vyas K, Tuch D, Giannarou S, Elson DS. 2020. Tracking and visualization of the sensing area for a tethered laparoscopic gamma probe. IJCARS. 15(8):1389–1397. doi:https://doi.org/10.1007/s11548-020-02205-z.
   Google Scholar
• Huynh DQ. 2009. Metrics for 3d rotations: comparison and analysis. J Math Imag Vis. 35(2):155–164. doi:https://doi.org/10.1007/s10851-009-0161-2.
   Google Scholar
• Jamjoom, Aimun AB, Ammer MA Jamjoom, and Hani J. Marcus. 2020. “Exploring public opinion about liability and responsibility in surgical robotics.„ Nature Machine Intelligence 2.4: 194–196.
   Google Scholar
• Jayarathne, U. L., McLeod, A. J., Peters, T. M., & Chen, E. C. (2013, September). Robust intraoperative US probe tracking using a monocular endoscopic camera. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 363–370). Springer, Berlin, Heidelberg.
   Google Scholar
• Jayarathne UL, Chen EC, Moore J, Peters TM. 2018. Robust, intrinsic tracking of a laparoscopic ultrasound probe for ultrasound-augmented laparoscopy. IEEE Trans Med Imag. 38(2):460–469. doi:https://doi.org/10.1109/TMI.2018.2866183.
   Google Scholar
• Kazanzides P, Chen Z, Deguet A, Fischer GS, Taylor RH, DiMaio SP. 2014. An open-source research kit for the da vinci surgical system. In: IEEE Intl. Conf. on Robotics and Auto. (ICRA); Hong Kong, China. p. 6434–6439.
   Google Scholar
• Kendall, Alex, Matthew Grimes, and Roberto Cipolla. 2015. “Posenet: A convolutional network for real-time 6-dof camera relocalization.„ In Proceedings of the IEEE international conference on computer vision, p. 2938–2946.
   Google Scholar
• Kopf, J., Rong, X. and Huang, J.B., 2021. Robust consistent video depth estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1611–1621.
   Google Scholar
• Lepetit V, Moreno-Noguer F, Fua P. 2009. Epnp: an accurate o (n) solution to the pnp problem. IJCV. 81(2):155. doi:https://doi.org/10.1007/s11263-008-0152-6.
   Google Scholar
• Liu X, Plishker W, Shekhar R. 2021. Hybrid electromagnetic-aruco tracking of laparoscopic ultrasound transducer in laparoscopic video. J Med Imag. 8(1):015001. doi:https://doi.org/10.1117/1.JMI.8.1.015001.
   Google Scholar
• Ma L, Wang J, Kiyomatsu H, Tsukihara H, Sakuma I, Kobayashi E. 2020. Surgical navigation system for laparoscopic lateral pelvic lymph node dissection in rectal cancer surgery using laparoscopic-vision-tracked ultrasonic imaging. Surg Endosc. 1–12. doi:https://doi.org/10.1007/s00464-020-08153-8.
   Google Scholar
• Mahendran, S., Ali, H. and Vidal, R., 2017. 3d pose regression using convolutional neural networks. In Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 2174–2182.
   Google Scholar
• Reiter, A., Allen, P.K. and Zhao, T., 2012, June. Articulated surgical tool detection using virtually-rendered templates. In Computer Assisted Radiology and Surgery (CARS), pp. 1–8.
   Google Scholar
• Reiter, A., Allen, P.K. and Zhao, T., 2012, October. Feature classification for tracking articulated surgical tools. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 592–600). Springer, Berlin, Heidelberg.
   Google Scholar
• Shao, J., Luo, H., Xiao, D., Hu, Q. and Jia, F., 2017. Progressive hand-eye calibration for laparoscopic surgery navigation. In Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures (pp. 42–49). Springer, Cham.
   Google Scholar
• Wang, T., Wang, Y. and Li, M., 2020, October. Towards accurate and interpretable surgical skill assessment: A video-based method incorporating recognized surgical gestures and skill levels. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 668–678). Springer, Cham.
   Google Scholar
• Wu SY, Aurup C, Sanchez CS, Grondin J, Zheng W, Kamimura H, Ferrera VP, Konofagou EE. 2018. Efficient blood-brain barrier opening in primates with neuronavigation-guided ultrasound and real-time acoustic mapping. Sci Rep. 8(1):1–11. doi:https://doi.org/10.1038/s41598-018-25904-9.
   Google Scholar
• Ye, M., Zhang, L., Giannarou, S. and Yang, G.Z., 2016, October. Real-time 3d tracking of articulated tools for robotic surgery. In International conference on medical image computing and computer-assisted intervention (pp. 386–394). Springer, Cham.
   Google Scholar
• Zhan, J., Cartucho, J. and Giannarou, S., 2020, May. Autonomous tissue scanning under free-form motion for intraoperative tissue characterisation. In 2020IEEE International Conference on Robotics and Automation(ICRA) (pp. 11147–11154). IEEE.
   Google Scholar
• Zhang, L., Ye, M., Chan, P.L. and Yang, G.Z., 2017. Real-time surgical tool tracking and pose estimation using a hybrid cylindrical marker. International journal of computer assisted radiology and surgery, 12(6), pp.921–930.
   Google Scholar
• Zhang L, Ye M, Chan PL, Yang GZ. 2017. Real-time surgical tool tracking and pose estimation using a hybrid cylindrical marker. IJCARS. 12(6):921–930. doi:https://doi.org/10.1007/s11548-017-1558-9.
   Google Scholar