Adaptive 3D pose computation of suturing needle using constraints from static monocular image feedback

Fangxun Zhong, David Navarro Alarcon, Zerui Wang, Yun Hui Liu, Tianxue Zhang, Hiu Man Yip, Hesheng Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)


In this paper, we address the problem of the image-based 3D pose computation of a semi-circle suturing needle using monocular image feedback for laparoscopy. We propose a constrained two-degree-of-freedom (2-DOF) geometrybased modelling method to parametrise the needle's 6-DOF pose, including depth information. The modelling solely relies on the simultaneous observation of the needle's apparent tip and junction. No external markers are needed for extra constraints. An adaptive controller combining gradient descent and vectorflow method is introduced to iteratively guide the needle's initial guessing pose to its real pose by minimizing image-based position errors. Experiments have been conducted using both numerical simulations and simulated laparoscopic scenarios to evaluate the performance of the algorithm.
Original languageEnglish
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
Number of pages6
ISBN (Electronic)9781509037629
Publication statusPublished - 28 Nov 2016
Externally publishedYes
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon Convention Center, Daejeon, Korea, Republic of
Duration: 9 Oct 201614 Oct 2016


Conference2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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