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: Aug 25, 2025

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:39

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

260

Medical decision support system using weakly-labeled lung CT scans.

Alejandro Murillo-González1, David González2, Laura Jaramillo2

  • 1Department of Mathematical Sciences, Universidad EAFIT, Medellín, Colombia.

Frontiers in Medical Technology
|October 17, 2022
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

Factors associated with severe health outcomes among community-dwelling older adults hospitalized with respiratory syncytial virus.

The Journal of infection·2026
Same author

Distinct volatile profiles of Metschnikowia pulcherrima L672 and Hanseniaspora uvarum L793 determine their antagonistic efficacy against Aspergillus flavus in a dried fig agar model.

International journal of food microbiology·2026
Same author

Sociodemographic and clinical determinants of general practice consultation frequency among regular patients in Australia: a national study.

BJGP open·2026
Same author

A mechanistic hypothesis: osteopathic manipulative therapy may modulate immune cell function in chronic low back pain.

Frontiers in pain research (Lausanne, Switzerland)·2026
Same author

The entactogen MDMA (3,4-methylenedioxymethamphetamine, "Ecstasy") disrupts helping behaviour while reinforcing electrophysiological indicators of potentially associated synaptic plasticity in male Sprague-Dawley rats.

Frontiers in pharmacology·2026
Same author

Exploratory association between multimodal AI-derived digital biomarkers and in-hospital mortality in adult patients with pneumonia: A proof-of-concept study.

PLOS digital health·2026

This study developed an AI system using Artificial Intelligence (AI) for COVID-19 patient diagnosis via CT scans. The AI accurately classifies lung conditions and quantifies lesions, aiding clinical decisions.

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Pulmonology

Background:

  • Accurate diagnosis of COVID-19 using medical imaging is crucial for patient management.
  • Artificial Intelligence (AI) offers potential for automating and improving diagnostic accuracy in radiology.
  • Computed Tomography (CT) scans are widely used for visualizing lung abnormalities.

Purpose of the Study:

  • To develop an effective AI-based system to support clinicians in diagnosing COVID-19 patients using axial lung CT studies.
  • To create a pipeline for classification, lung segmentation, lesion segmentation, and lesion quantification.
  • To leverage AI techniques for efficient and accurate analysis of lung CT data.

Main Methods:

  • A deep neural network architecture based on DenseNet was employed for classifying CT scans.
Keywords:
computational tomographylesion segmentation / quantificationmachine learningvolume classificationweak-labels

More Related Videos

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.0K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.3K

Related Experiment Videos

Last Updated: Aug 25, 2025

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:39

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

260
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.0K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.3K
  • The models were trained on aggregated public datasets and a diverse dataset from Colombian medical institutions (1,322 CT studies).
  • A methodology for segmenting and quantifying lesions in COVID-19 patients was developed and integrated into the pipeline.

    • Main Results:

    • The classification models achieved high performance: 0.83 accuracy (Normal vs. Abnormal) and 0.86 accuracy (Abnormal vs. COVID-19).
    • Sensitivity, specificity, F1 score, and precision metrics demonstrated robust classification capabilities.
    • Ablation studies confirmed that utilizing the complete CT study improved classification performance.

    Conclusions:

    • The developed AI architecture effectively handles weakly-labeled, variable-sized, and sparse axial lung CT studies.
    • The system reduces the need for extensive expert annotations at a per-slice level.
    • This methodology can guide the development of AI-driven decision support systems for clinical practice and future studies.