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

Quantitative dynamic full-field optical coherence tomography for high-resolution intraoperative imaging of head and neck squamous cell carcinoma.

Biomedical optics express·2026
Same author

Single-cell and spatial transcriptomic analysis reveal distinct tumor microenvironment signatures in primary and recurrent hypopharyngeal squamous cell carcinoma.

Cellular & molecular biology letters·2026
Same author

Preoperative health status assessed with different scales and postoperative cardiac and cerebrovascular complications in older patients: A retrospective study of a large multicentre cohort.

European journal of anaesthesiology·2026
Same author

Ketamine alters the aperiodic EEG exponent in major depression: implications for cortical E/I balance and treatment prediction.

Therapeutic advances in psychopharmacology·2026
Same author

Endoscopic transcervical mediastinal drainage for treating descending necrotizing mediastinitis.

BMC surgery·2026
Same author

Mutant superoxide dismutase 1-catalyzed hydrogen therapy for amyotrophic lateral sclerosis achieved by intercepting oxidative stress-neuroinflammation crosstalk.

Acta biomaterialia·2026

Related Experiment Video

Updated: May 24, 2025

Learning Modern Laryngeal Surgery in a Dissection Laboratory
07:30

Learning Modern Laryngeal Surgery in a Dissection Laboratory

Published on: March 18, 2020

7.9K

3D-LSPTM: An Automatic Framework with 3D-Large-Scale Pretrained Model for Laryngeal Cancer Detection Using

Meiyu Qiu, Yun Li, Wenjun Huang

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 3, 2025
    PubMed
    Summary

    This study introduces 3D-LSPTM, an automated framework using 3D-large-scale pretrained models for detecting laryngeal cancer from videos. The model achieves high accuracy, offering a faster and more objective alternative to manual inspection.

    More Related Videos

    Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
    07:53

    Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

    Published on: October 13, 2023

    1.3K
    Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
    05:41

    Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

    Published on: February 9, 2024

    518

    Related Experiment Videos

    Last Updated: May 24, 2025

    Learning Modern Laryngeal Surgery in a Dissection Laboratory
    07:30

    Learning Modern Laryngeal Surgery in a Dissection Laboratory

    Published on: March 18, 2020

    7.9K
    Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
    07:53

    Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

    Published on: October 13, 2023

    1.3K
    Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
    05:41

    Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

    Published on: February 9, 2024

    518

    Area of Science:

    • Otorhinolaryngology
    • Medical Imaging
    • Artificial Intelligence

    Background:

    • Laryngeal cancer poses a significant health threat with high mortality.
    • Manual visual inspection of laryngoscopic videos for diagnosis is time-consuming and subjective.

    Purpose of the Study:

    • To develop and evaluate an automated framework, 3D-LSPTM, for accurate laryngeal cancer detection.
    • To leverage 3D-large-scale pretrained models for enhanced video feature extraction.

    Main Methods:

    • Collected 1,109 laryngoscopic videos for training and testing.
    • Utilized and fine-tuned 3D-large-scale pretrained models: C3D, TimeSformer, and Video-Swin-Transformer.
    • Developed the 3D-LSPTM framework for automatic laryngeal cancer detection.

    Main Results:

    • The 3D-LSPTM framework demonstrated promising performance in laryngeal cancer detection.
    • The Video-Swin-Transformer backbone achieved 92.4% accuracy, 95.6% sensitivity, 94.1% precision, and 94.8% F1-score.
    • The automated approach offers improved efficiency and objectivity over manual methods.

    Conclusions:

    • The proposed 3D-LSPTM framework effectively automates laryngeal cancer detection using advanced pretrained models.
    • This AI-driven approach shows significant potential to improve diagnostic accuracy and efficiency in otorhinolaryngology.
    • Further validation with larger datasets could solidify its clinical utility.