Event-based patient motion detection and compensation in image-guided robotics

Tamas Haidegger, Peter Kazanzides, Balazs Benyo, Z. Benyó

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We report a generalized approach to deal with patient motion in robotic image-guided surgery, along with in silico and dry laboratory tests on a neurosurgical robot setup. External patient motion events (excluding physiological motion) can occur during surgery despite body fixation, and can endanger the outcome of the surgery, as they invalidate the registration between the robot and the patient. The core of the compensation algorithm is to rely on the combination of the robot joint encoders, tracking data and the internal coordinate frame of the intra-operative navigation system to ensure accurate execution of the pre-operative plan. The method allows for the continuous correction of the registration through identifying the actual surgical event in the operating room. From the control point of view, the intra-operative events have been categorized as robot motion, camera motion, patient motion and the combinations of these. The registration update is based on the use of the most reliable reference frame and extending-window averaging to compensate for the occurred patient motion. Simulation results were performed on a generic image-guided robot model, and on a skull base surgery robot. Patient motion events were detected in 80% of the cases, which already leads to a gradual improvement of the procedure. The proposed structure allows for a more generic, probability-based handling of the operating room events that may lead to safer and more accurate surgical treatment in the future.

Original languageEnglish
Title of host publicationProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Pages841-846
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012 - Rome, Italy
Duration: Jun 24 2012Jun 27 2012

Other

Other2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012
CountryItaly
CityRome
Period6/24/126/27/12

Fingerprint

Robotics
Robots
Surgery
Operating rooms
Navigation systems
Compensation and Redress
Cameras

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

Cite this

Haidegger, T., Kazanzides, P., Benyo, B., & Benyó, Z. (2012). Event-based patient motion detection and compensation in image-guided robotics. In Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (pp. 841-846). [6290257] https://doi.org/10.1109/BioRob.2012.6290257

Event-based patient motion detection and compensation in image-guided robotics. / Haidegger, Tamas; Kazanzides, Peter; Benyo, Balazs; Benyó, Z.

Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics. 2012. p. 841-846 6290257.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Haidegger, T, Kazanzides, P, Benyo, B & Benyó, Z 2012, Event-based patient motion detection and compensation in image-guided robotics. in Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics., 6290257, pp. 841-846, 2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012, Rome, Italy, 6/24/12. https://doi.org/10.1109/BioRob.2012.6290257
Haidegger T, Kazanzides P, Benyo B, Benyó Z. Event-based patient motion detection and compensation in image-guided robotics. In Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics. 2012. p. 841-846. 6290257 https://doi.org/10.1109/BioRob.2012.6290257
Haidegger, Tamas ; Kazanzides, Peter ; Benyo, Balazs ; Benyó, Z. / Event-based patient motion detection and compensation in image-guided robotics. Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics. 2012. pp. 841-846
@inproceedings{972e556f471c4337a53812cbb0fadcff,
title = "Event-based patient motion detection and compensation in image-guided robotics",
abstract = "We report a generalized approach to deal with patient motion in robotic image-guided surgery, along with in silico and dry laboratory tests on a neurosurgical robot setup. External patient motion events (excluding physiological motion) can occur during surgery despite body fixation, and can endanger the outcome of the surgery, as they invalidate the registration between the robot and the patient. The core of the compensation algorithm is to rely on the combination of the robot joint encoders, tracking data and the internal coordinate frame of the intra-operative navigation system to ensure accurate execution of the pre-operative plan. The method allows for the continuous correction of the registration through identifying the actual surgical event in the operating room. From the control point of view, the intra-operative events have been categorized as robot motion, camera motion, patient motion and the combinations of these. The registration update is based on the use of the most reliable reference frame and extending-window averaging to compensate for the occurred patient motion. Simulation results were performed on a generic image-guided robot model, and on a skull base surgery robot. Patient motion events were detected in 80{\%} of the cases, which already leads to a gradual improvement of the procedure. The proposed structure allows for a more generic, probability-based handling of the operating room events that may lead to safer and more accurate surgical treatment in the future.",
author = "Tamas Haidegger and Peter Kazanzides and Balazs Benyo and Z. Beny{\'o}",
year = "2012",
doi = "10.1109/BioRob.2012.6290257",
language = "English",
isbn = "9781457711992",
pages = "841--846",
booktitle = "Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics",

}

TY - GEN

T1 - Event-based patient motion detection and compensation in image-guided robotics

AU - Haidegger, Tamas

AU - Kazanzides, Peter

AU - Benyo, Balazs

AU - Benyó, Z.

PY - 2012

Y1 - 2012

N2 - We report a generalized approach to deal with patient motion in robotic image-guided surgery, along with in silico and dry laboratory tests on a neurosurgical robot setup. External patient motion events (excluding physiological motion) can occur during surgery despite body fixation, and can endanger the outcome of the surgery, as they invalidate the registration between the robot and the patient. The core of the compensation algorithm is to rely on the combination of the robot joint encoders, tracking data and the internal coordinate frame of the intra-operative navigation system to ensure accurate execution of the pre-operative plan. The method allows for the continuous correction of the registration through identifying the actual surgical event in the operating room. From the control point of view, the intra-operative events have been categorized as robot motion, camera motion, patient motion and the combinations of these. The registration update is based on the use of the most reliable reference frame and extending-window averaging to compensate for the occurred patient motion. Simulation results were performed on a generic image-guided robot model, and on a skull base surgery robot. Patient motion events were detected in 80% of the cases, which already leads to a gradual improvement of the procedure. The proposed structure allows for a more generic, probability-based handling of the operating room events that may lead to safer and more accurate surgical treatment in the future.

AB - We report a generalized approach to deal with patient motion in robotic image-guided surgery, along with in silico and dry laboratory tests on a neurosurgical robot setup. External patient motion events (excluding physiological motion) can occur during surgery despite body fixation, and can endanger the outcome of the surgery, as they invalidate the registration between the robot and the patient. The core of the compensation algorithm is to rely on the combination of the robot joint encoders, tracking data and the internal coordinate frame of the intra-operative navigation system to ensure accurate execution of the pre-operative plan. The method allows for the continuous correction of the registration through identifying the actual surgical event in the operating room. From the control point of view, the intra-operative events have been categorized as robot motion, camera motion, patient motion and the combinations of these. The registration update is based on the use of the most reliable reference frame and extending-window averaging to compensate for the occurred patient motion. Simulation results were performed on a generic image-guided robot model, and on a skull base surgery robot. Patient motion events were detected in 80% of the cases, which already leads to a gradual improvement of the procedure. The proposed structure allows for a more generic, probability-based handling of the operating room events that may lead to safer and more accurate surgical treatment in the future.

UR - http://www.scopus.com/inward/record.url?scp=84867436051&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867436051&partnerID=8YFLogxK

U2 - 10.1109/BioRob.2012.6290257

DO - 10.1109/BioRob.2012.6290257

M3 - Conference contribution

AN - SCOPUS:84867436051

SN - 9781457711992

SP - 841

EP - 846

BT - Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics

ER -