• DocumentCode
    2472387
  • Title

    Sensors management in robotic neurosurgery: The ROBOCAST project

  • Author

    Vaccarella, Alberto ; Comparetti, Mirko Daniele ; Enquobahrie, Andinet ; Ferrigno, Giancarlo ; De Momi, Elena

  • Author_Institution
    Bioeng. Dept., Politec. di Milano, Milan, Italy
  • fYear
    2011
  • fDate
    Aug. 30 2011-Sept. 3 2011
  • Firstpage
    2119
  • Lastpage
    2122
  • Abstract
    Robot and computer-aided surgery platforms bring a variety of sensors into the operating room. These sensors generate information to be synchronized and merged for improving the accuracy and the safety of the surgical procedure for both patients and operators. In this paper, we present our work on the development of a sensor management architecture that is used is to gather and fuse data from localization systems, such as optical and electromagnetic trackers and ultrasound imaging devices. The architecture follows a modular client-server approach and was implemented within the EU-funded project ROBOCAST (FP7 ICT 215190). Furthermore it is based on very well-maintained open-source libraries such as OpenCV and Image-Guided Surgery Toolkit (IGSTK), which are supported from a worldwide community of developers and allow a significant reduction of software costs. We conducted experiments to evaluate the performance of the sensor manager module. We computed the response time needed for a client to receive tracking data or video images, and the time lag between synchronous acquisition with an optical tracker and ultrasound machine. Results showed a median delay of 1.9 ms for a client request of tracking data and about 40 ms for US images; these values are compatible with the data generation rate (20-30 Hz for tracking system and 25 fps for PAL video). Simultaneous acquisitions have been performed with an optical tracking system and US imaging device: data was aligned according to the timestamp associated with each sample and the delay was estimated with a cross-correlation study. A median value of 230 ms delay was calculated showing that realtime 3D reconstruction is not feasible (an offline temporal calibration is needed), although a slow exploration is possible. In conclusion, as far as asleep patient neurosurgery is concerned, the proposed setup is indeed useful for registration error correction because the brain shift occurs with a time constant of few tens of minutes.
  • Keywords
    biomedical ultrasonics; image registration; medical image processing; medical robotics; neurophysiology; surgery; ultrasonic imaging; Image Guided Surgery Toolkit; OpenCV; PAL video; ROBOCAST project; computer aided surgery; delay; electromagnetic trackers; optical trackers; realtime 3D reconstruction; registration error correction; robotic neurosurgery; sensors management; surgical procedure accuracy; surgical procedure safety; ultrasound imaging devices; Optical imaging; Optical sensors; Robot sensing systems; Surgery; Ultrasonic imaging; Equipment Design; Equipment Failure Analysis; Humans; Neurosurgical Procedures; Reproducibility of Results; Robotics; Sensitivity and Specificity; Surgery, Computer-Assisted; Transducers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
  • Conference_Location
    Boston, MA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4121-1
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2011.6090395
  • Filename
    6090395