Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Dec 20, 2025

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

3.4K

i3PosNet: instrument pose estimation from X-ray in temporal bone surgery.

David Kügler1,2, Jannik Sehring3, Andrei Stefanov3

  • 1Department of Computer Science, Technischer Universität Darmstadt, Darmstadt, Germany. david.kuegler@dzne.de.

International Journal of Computer Assisted Radiology and Surgery
|May 23, 2020
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

NORG - Nitrogen ORGanizer: a novel web-based system for cryopreservation and freezer management.

Database : the journal of biological databases and curation·2026
Same author

The role of perceived competence in remote cochlear implant aftercare: a mixed-methods study.

Frontiers in digital health·2026
Same author

Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.

Nature cancer·2026
Same author

Learning-based segmentation of diffusion-weighted MR images with arbitrary <i>q</i>-space samplings.

Imaging neuroscience (Cambridge, Mass.)·2026
Same author

Vascularized anterolateral thigh free flap for salvage reconstruction of complex anterior skull base and nasion defects after failed conventional reconstruction- how I do it.

Acta neurochirurgica·2026
Same author

Real-time planar angiographic cerebral perfusion imaging.

International journal of computer assisted radiology and surgery·2026

i3PosNet accurately estimates surgical instrument pose using deep learning on X-ray images. This method achieves sub-millimeter accuracy, outperforming traditional techniques without ionizing radiation.

Area of Science:

  • Medical Imaging
  • Surgical Navigation
  • Deep Learning

Background:

  • Accurate surgical instrument pose estimation is vital for minimally invasive temporal bone surgery.
  • Conventional tracking systems have accuracy limitations or line-of-sight constraints.
  • Intra-operative CT poses risks due to ionizing radiation.

Purpose of the Study:

  • To develop and evaluate i3PosNet, a novel deep learning framework for surgical instrument pose estimation from c-arm X-ray images.
  • To overcome limitations of existing tracking methods in accuracy and radiation exposure.
  • To enable pose recovery from irregularly captured images.

Main Methods:

  • i3PosNet utilizes a pose estimation network to infer instrument position and orientation from images.
Keywords:
Cochlear implantFluoroscopic trackingMinimally invasive bone surgeryModular deep learningVestibular schwannoma removalinstrument pose estimation

More Related Videos

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.2K

Related Experiment Videos

Last Updated: Dec 20, 2025

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
07:43

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

3.4K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.2K
  • The framework employs localized image patches and outputs pseudo-landmarks.
  • Pose reconstruction is achieved through geometric principles applied to the pseudo-landmarks.

    • Main Results:

    • i3PosNet achieves sub-millimeter pose estimation errors.
    • The method significantly outperforms conventional image registration approaches, reducing errors by at least two-thirds.
    • i3PosNet demonstrates generalization from synthetic training data to real X-ray images without fine-tuning.

    Conclusions:

    • Deep learning translation to surgical applications is challenging due to limited datasets.
    • This study empirically validates sub-millimeter pose estimation using only synthetic training data.
    • i3PosNet offers a promising, radiation-free solution for surgical instrument tracking.