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

Semiautomatic method for peak velocity quantification using 4D flow imaging in hypertrophic cardiomyopathy with left ventricular outflow tract obstruction.

European journal of radiology·2026
Same author

A rare cause of acute abdominal pain in pregnancy: Right adrenal vein thrombosis with unilateral adrenal infarction.

Vascular diseases (Paris, France)·2026
Same author

Characteristics of lung nodules detected by low-dose CT scan: Results from the French lung cancer screening study DEP KP-80.

Respiratory medicine and research·2026
Same author

Quantification of pulmonary arterial pressure with 4D flow cardiac MRI velocity mapping in patients with suspected pulmonary hypertension: Comparison with right heart catheterization.

PloS one·2026
Same author

Dynamic Computed Tomography Angiography for the Characterisation of Endoleaks after Endovascular Aneurysm Repair: Development and Feasibility of a Standardised Cine Protocol.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery·2026
Same author

Comparison of oral water ingestion and intravenous fluid infusion on fluid responsiveness in healthy volunteers, a prospective, randomized trial.

Scientific reports·2026

Related Experiment Video

Updated: Sep 24, 2025

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

Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

Fabrice Ferri1, Roger Bouzerar2, Marianne Auquier1

  • 1Department of Radiology, Amiens University Hospital, 1 Rond-Point du Professeur Christian Cabrol, F-80054 Amiens Cedex 01, France.

European Journal of Radiology
|May 9, 2022
PubMed
Summary

Deep learning image reconstruction (DLIR) significantly impacts emphysema volume quantification in low-dose CT scans. DLIR-H closely correlates with filtered FBP, improving signal-to-noise ratio while reducing noise.

Keywords:
Chronic obstructive pulmonary diseaseComputed tomographyDeep learning image reconstructionPulmonary emphysema

More Related Videos

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

692
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

642

Related Experiment Videos

Last Updated: Sep 24, 2025

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
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

692
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

642

Area of Science:

  • Radiology
  • Medical Imaging
  • Pulmonary Medicine

Background:

  • Quantitative analysis of emphysema volume is crucial for diagnosing and managing Chronic Obstructive Pulmonary Disease (COPD).
  • CT reconstruction techniques and radiation dose influence emphysema quantification accuracy.
  • Deep learning image reconstruction (DLIR) algorithms offer potential improvements in image quality and quantitative analysis.

Purpose of the Study:

  • To evaluate the impact of a commercial deep learning image reconstruction (DLIR) algorithm on pulmonary emphysema volume quantification.
  • To compare DLIR performance against traditional filtered back projection (FBP) and iterative reconstruction (ASIR-V) in low-dose chest CT.

Main Methods:

  • Retrospective analysis of low-dose chest CT scans from 54 COPD patients.
  • Reconstruction of raw data using Filtered Back Projection (FBP), ASIR-V (70%), and DLIR at high, medium, and low strengths (DLIR-H, DLIR-M, DLIR-L).
  • Measurement of pulmonary emphysema volume (voxels < -950 HU) and assessment of image quality (SNR, noise) in different regions.

Main Results:

  • Significant differences in emphysema volumes were observed between FBP, ASIR-V, and all DLIR strengths (p < 10⁻³).
  • DLIR-H demonstrated a strong correlation with filtered FBP (r = 0.999, p < 10⁻⁴), with a 10% overestimation.
  • DLIR-H significantly reduced noise and improved signal-to-noise ratio (SNR) compared to other methods (p < 10⁻⁶).

Conclusions:

  • DLIR algorithms introduce significant differences in emphysema volume quantification compared to FBP and iterative reconstruction.
  • DLIR-H provides the closest correlation to filtered FBP for emphysema volume measurement.
  • DLIR-H enhances image quality by reducing noise and increasing SNR in low-dose CT scans for COPD assessment.