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

Revealing the correlation between chemical composition and pharmacological effects of medicinal plants in the Ilex L. genus.

Fitoterapia·2026
Same author

Decoding and reconstructing yeast protein flavor based on an integrated sensory-omics approach.

Food chemistry: X·2026
Same author

Competitive secondary formation and evolving sources drive the stage-dependent evolution of PM<sub>2.5</sub>-bound PAHs and their derivatives associated health risks.

Journal of hazardous materials·2026
Same author

Confinement-Modulated Proton-Transfer Kinetics in Graphene and Graphene-Oxide Nanochannels: A Markovian Statistical Framework.

The journal of physical chemistry. B·2026
Same author

GMC-Bind: A Multimodal Framework for RNA-Protein Binding Site Prediction with Bidirectional Cross-Attentional Fusion.

IEEE transactions on computational biology and bioinformatics·2026
Same author

CLIS: Causality-inspired Longitudinal Image Synthesis and its application to Alzheimer's disease characterization.

Medical image analysis·2026

Related Experiment Video

Updated: Jun 7, 2025

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
12:30

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures

Published on: July 2, 2014

20.3K

LACOSTE: Exploiting stereo and temporal contexts for surgical instrument segmentation.

Qiyuan Wang1, Shang Zhao1, Zikang Xu1

  • 1School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei Anhui, 230026, P.R. China; Center for Medical Imaging, Robotics, Analytic Computing & Learning(MIRACLE), Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu, 215123, P.R. China.

Medical Image Analysis
|November 17, 2024
PubMed
Summary

This study introduces the LACOSTE model for surgical instrument segmentation, enhancing robustness by utilizing stereo and temporal contexts. The novel approach improves accuracy in minimally invasive surgeries.

Keywords:
Query-based segmentationSet classifierStereo-temporal modelingSurgical data scienceTransformer

More Related Videos

Building An Open-source Robotic Stereotaxic Instrument
11:40

Building An Open-source Robotic Stereotaxic Instrument

Published on: October 29, 2013

14.9K
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

2.0K

Related Experiment Videos

Last Updated: Jun 7, 2025

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
12:30

A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures

Published on: July 2, 2014

20.3K
Building An Open-source Robotic Stereotaxic Instrument
11:40

Building An Open-source Robotic Stereotaxic Instrument

Published on: October 29, 2013

14.9K
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

2.0K

Area of Science:

  • Computer Vision
  • Medical Imaging
  • Robotics

Background:

  • Surgical instrument segmentation is crucial for minimally invasive surgery.
  • Existing methods often fail due to temporal motion and view changes.
  • Single-frame segmentation ignores valuable temporal and stereo information.

Purpose of the Study:

  • To develop a robust surgical instrument segmentation model.
  • To leverage stereo and temporal information for improved accuracy.
  • To address limitations of single-frame segmentation methods.

Main Methods:

  • Proposed the LACOSTE (Location-Agnostic COntexts in Stereo and TEmporal images) model.
  • Implemented a disparity-guided feature propagation module with a pseudo stereo scheme.
  • Introduced a stereo-temporal set classifier and a location-agnostic classifier.

Main Results:

  • LACOSTE demonstrated improved robustness against appearance variations.
  • The model achieved comparable or favorable results on public datasets.
  • Validated on EndoVis Challenges and GraSP datasets.

Conclusions:

  • The LACOSTE model effectively utilizes stereo and temporal contexts for surgical instrument segmentation.
  • The proposed modules enhance feature representation and prediction accuracy.
  • This approach offers a more robust solution for surgical video analysis.