3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

51 Citations (Scopus)

Abstract

Needle insertion procedures are commonly used for surgical interventions. In this paper, we develop a three-dimensional (3D) closed-loop control algorithm to robotically steer flexible needles with an asymmetric tip towards a target in a soft-tissue phantom. Twelve Fiber Bragg Grating (FBG) sensors are embedded on the needle shaft. FBG sensors measure the strain applied on the needle during insertion. A method is developed to reconstruct the needle shape using the strain data obtained from the FBG sensors. Four experimental cases are conducted to validate the reconstruction method (single-bend, double-bend, 3D double-bend and drilling insertions). In the experiments, the needle is inserted 120 mm into a soft-tissue phantom. Camera images are used as a reference for the reconstruction experiments. The results show that the mean needle tip accuracy of the reconstruction method is 1.8 mm. The reconstructed needle shape is used as feedback for the steering algorithm. The steering algorithm estimates the region that the needle can reach during insertion, and controls the needle to keep the target in this region. Steering experiments are performed for 110 mm insertion, and the mean targeting accuracy is 1.3 mm. The results demonstrate the capability of using FBG sensors to robotically steer needles.
Original languageUndefined
Title of host publicationProceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013
Place of PublicationUSA
PublisherIEEE ROBOTICS AND AUTOMATION SOCIETY
Pages5843-5849
Number of pages7
ISBN (Print)978-1-4673-5641-1
DOIs
Publication statusPublished - 6 May 2013
Event2013 IEEE International Conference on Robotics and Automation, ICRA 2013 - Karlsruhe, Germany
Duration: 6 May 201310 May 2013

Publication series

NameIEEE RAS
PublisherIEEE Robotics and Automation Society
ISSN (Print)1050-4729

Conference

Conference2013 IEEE International Conference on Robotics and Automation, ICRA 2013
Abbreviated titleICRA
CountryGermany
CityKarlsruhe
Period6/05/1310/05/13

Keywords

  • EWI-24479
  • METIS-302708
  • IR-89495

Cite this

Abayazid, M., Kemp, M., & Misra, S. (2013). 3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors. In Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013 (pp. 5843-5849). (IEEE RAS). USA: IEEE ROBOTICS AND AUTOMATION SOCIETY. https://doi.org/10.1109/ICRA.2013.6631418
Abayazid, Momen ; Kemp, Marco ; Misra, Sarthak. / 3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors. Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013. USA : IEEE ROBOTICS AND AUTOMATION SOCIETY, 2013. pp. 5843-5849 (IEEE RAS).
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title = "3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors",
abstract = "Needle insertion procedures are commonly used for surgical interventions. In this paper, we develop a three-dimensional (3D) closed-loop control algorithm to robotically steer flexible needles with an asymmetric tip towards a target in a soft-tissue phantom. Twelve Fiber Bragg Grating (FBG) sensors are embedded on the needle shaft. FBG sensors measure the strain applied on the needle during insertion. A method is developed to reconstruct the needle shape using the strain data obtained from the FBG sensors. Four experimental cases are conducted to validate the reconstruction method (single-bend, double-bend, 3D double-bend and drilling insertions). In the experiments, the needle is inserted 120 mm into a soft-tissue phantom. Camera images are used as a reference for the reconstruction experiments. The results show that the mean needle tip accuracy of the reconstruction method is 1.8 mm. The reconstructed needle shape is used as feedback for the steering algorithm. The steering algorithm estimates the region that the needle can reach during insertion, and controls the needle to keep the target in this region. Steering experiments are performed for 110 mm insertion, and the mean targeting accuracy is 1.3 mm. The results demonstrate the capability of using FBG sensors to robotically steer needles.",
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Abayazid, M, Kemp, M & Misra, S 2013, 3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors. in Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013. IEEE RAS, IEEE ROBOTICS AND AUTOMATION SOCIETY, USA, pp. 5843-5849, 2013 IEEE International Conference on Robotics and Automation, ICRA 2013, Karlsruhe, Germany, 6/05/13. https://doi.org/10.1109/ICRA.2013.6631418

3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors. / Abayazid, Momen; Kemp, Marco; Misra, Sarthak.

Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013. USA : IEEE ROBOTICS AND AUTOMATION SOCIETY, 2013. p. 5843-5849 (IEEE RAS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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T1 - 3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors

AU - Abayazid, Momen

AU - Kemp, Marco

AU - Misra, Sarthak

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PY - 2013/5/6

Y1 - 2013/5/6

N2 - Needle insertion procedures are commonly used for surgical interventions. In this paper, we develop a three-dimensional (3D) closed-loop control algorithm to robotically steer flexible needles with an asymmetric tip towards a target in a soft-tissue phantom. Twelve Fiber Bragg Grating (FBG) sensors are embedded on the needle shaft. FBG sensors measure the strain applied on the needle during insertion. A method is developed to reconstruct the needle shape using the strain data obtained from the FBG sensors. Four experimental cases are conducted to validate the reconstruction method (single-bend, double-bend, 3D double-bend and drilling insertions). In the experiments, the needle is inserted 120 mm into a soft-tissue phantom. Camera images are used as a reference for the reconstruction experiments. The results show that the mean needle tip accuracy of the reconstruction method is 1.8 mm. The reconstructed needle shape is used as feedback for the steering algorithm. The steering algorithm estimates the region that the needle can reach during insertion, and controls the needle to keep the target in this region. Steering experiments are performed for 110 mm insertion, and the mean targeting accuracy is 1.3 mm. The results demonstrate the capability of using FBG sensors to robotically steer needles.

AB - Needle insertion procedures are commonly used for surgical interventions. In this paper, we develop a three-dimensional (3D) closed-loop control algorithm to robotically steer flexible needles with an asymmetric tip towards a target in a soft-tissue phantom. Twelve Fiber Bragg Grating (FBG) sensors are embedded on the needle shaft. FBG sensors measure the strain applied on the needle during insertion. A method is developed to reconstruct the needle shape using the strain data obtained from the FBG sensors. Four experimental cases are conducted to validate the reconstruction method (single-bend, double-bend, 3D double-bend and drilling insertions). In the experiments, the needle is inserted 120 mm into a soft-tissue phantom. Camera images are used as a reference for the reconstruction experiments. The results show that the mean needle tip accuracy of the reconstruction method is 1.8 mm. The reconstructed needle shape is used as feedback for the steering algorithm. The steering algorithm estimates the region that the needle can reach during insertion, and controls the needle to keep the target in this region. Steering experiments are performed for 110 mm insertion, and the mean targeting accuracy is 1.3 mm. The results demonstrate the capability of using FBG sensors to robotically steer needles.

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BT - Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013

PB - IEEE ROBOTICS AND AUTOMATION SOCIETY

CY - USA

ER -

Abayazid M, Kemp M, Misra S. 3D flexible needle steering in soft-tissue phantoms using fiber bragg grating sensors. In Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2013. USA: IEEE ROBOTICS AND AUTOMATION SOCIETY. 2013. p. 5843-5849. (IEEE RAS). https://doi.org/10.1109/ICRA.2013.6631418