Image-based tracking of the suturing needle during laparoscopic interventions

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • S. Speidel - , Karlsruhe Institute of Technology (Author)
  • A. Kroehnert - , Karlsruhe Institute of Technology (Author)
  • S. Bodenstedt - , Karlsruhe Institute of Technology (Author)
  • H. Kenngott - , Heidelberg University  (Author)
  • B. Müller-Stich - , Heidelberg University  (Author)
  • R. Dillmann - , Karlsruhe Institute of Technology (Author)

Abstract

One of the most complex and difficult tasks for surgeons during minimally invasive interventions is suturing. A prerequisite to assist the suturing process is the tracking of the needle. The endoscopic images provide a rich source of information which can be used for needle tracking. In this paper, we present an image-based method for markerless needle tracking. The method uses a color-based and geometry-based segmentation to detect the needle. Once an initial needle detection is obtained, a region of interest enclosing the extracted needle contour is passed on to a reduced segmentation. It is evaluated with in vivo images from da Vinci interventions.

Details

Original languageEnglish
Title of host publicationMedical Imaging 2015
EditorsRobert J. Webster, Ziv R. Yaniv
PublisherSPIE - The international society for optics and photonics, Bellingham
ISBN (electronic)9781628415056
Publication statusPublished - 2015
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9415
ISSN1605-7422

Conference

TitleMedical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Duration22 - 24 February 2015
CityOrlando
CountryUnited States of America

External IDs

ORCID /0000-0002-4590-1908/work/163294122

Keywords

Keywords

  • Endoscopic image processing, Laparoscopic procedures, Localization & tracking technologies, Robotic-assisted surgery, Surgical vision