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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Initial Experience With a Deep Learning Algorithm for Detecting Posterior Circulation Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke (Hoboken, N.J.)·2026
Same author

Whitening black boxes: Interpretable and explainable DL-based systems for trustworthy healthcare.

Artificial intelligence in medicine·2026
Same author

Action units of facial expressions in emotional contagion.

iScience·2026
Same author

A mixed reality framework for interpretable and explainable joint replacement assessment.

International journal of medical informatics·2026
Same author

Advancing surgical cutting guide flexibility: A hybrid physical and Augmented Reality solution for cranio-maxillofacial surgery.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery·2026
Same author

A 3D Camera-Based Approach for Real-Time Hand Configuration Recognition in Italian Sign Language.

Sensors (Basel, Switzerland)·2026

Related Experiment Video

Updated: Oct 1, 2025

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
10:25

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

Published on: September 2, 2025

85

A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery.

Erica Padovan1, Giorgia Marullo1, Leonardo Tanzi1

  • 1Department of Management, Production and Design Engineering, Polytechnic University of Turin, Turin, Italy.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS
|March 5, 2022
PubMed
Summary

This study introduces a deep learning framework for real-time organ position and rotation tracking during endoscopic surgery, enhancing augmented reality guidance for surgeons. It marks a step towards generalized automatic registration in robotic procedures.

Keywords:
Kidneyabdominalprostate

More Related Videos

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.2K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

872

Related Experiment Videos

Last Updated: Oct 1, 2025

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
10:25

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation

Published on: September 2, 2025

85
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

2.2K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

872

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Surgical Robotics

Background:

  • Real-time organ position and rotation tracking is crucial for surgical navigation.
  • Augmented reality (AR) overlays 3D models onto endoscopic video for enhanced surgical support.
  • Laparoscopic robot-assisted surgery benefits from improved visualization and guidance.

Purpose of the Study:

  • To develop a deep learning framework for real-time organ pose estimation from endoscopic video.
  • To enable accurate 3D model overlay for augmented reality surgical guidance.
  • To support surgeons during laparoscopic robot-assisted procedures.

Main Methods:

  • Utilized semantic segmentation for organ identification.
  • Employed Convolutional Neural Networks (CNNs) and motion analysis for rotation inference.
  • Integrated position and rotation data for real-time AR visualization.

Main Results:

  • Achieved optimal semantic segmentation accuracy with a mean IoU score over 80%.
  • Demonstrated variable rotation inference performance based on specific surgical procedures.
  • Successfully generated an augmented video stream for surgical support.

Conclusions:

  • The developed deep learning framework represents a foundational step for automated registration in surgery.
  • While precision varies with the scenario, the methodology shows promise for integrating AI and AR.
  • This work paves the way for generalizing automatic registration processes using deep learning and augmented reality.