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: May 17, 2026

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

A fully automatic method for lung parenchyma segmentation and repairing.

Ying Wei1, Guo Shen, Juan-juan Li

  • 1College of Information Science and Engineering, Northeastern University, No. 3 Wenhua Road, P.O. Box 128, Shenyang, 110004, People's Republic of China. weiying@ise.neu.edu.cn

Journal of Digital Imaging
|October 12, 2012
PubMed
Summary
This summary is machine-generated.

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

Immediate effect of acupuncture on pelvic floor muscles function for stress urinary incontinence in women: study protocol for a randomized and sham-controlled trial.

Frontiers in medicine·2026
Same author

Study on the low-frequency bandgap characteristics of the microsphere array three-dimensional phononic crystal.

The Journal of the Acoustical Society of America·2026
Same author

Expanding the genetic spectra of gyrate atrophy of the choroid and retina in a Chinese cohort in Yunnan province.

Human genomics·2025
Same author

Impaired Topological Architecture of Structural Brain Networks in Obstructive Sleep Apnea: A DTI Study.

Nature and science of sleep·2025
Same author

Enhanced Antitumor Efficacy and Reduced Myelosuppression by a Supramolecular Complex Composed of Azocalix[4]arene and Sunitinib.

Journal of medicinal chemistry·2025
Same author

Features and functional mechanisms of super-enhancers in cardiovascular disorders, cancer, autoimmune diseases and neurodegenerative disorders.

Cellular signalling·2025

This study introduces an automatic lung segmentation method that accurately segments lung parenchyma and juxtapleural nodules. The novel approach improves upon traditional methods, achieving high accuracy and speed for thoracic computed tomography scans.

Area of Science:

  • Medical Imaging
  • Computer-Aided Diagnosis
  • Radiology

Background:

  • Traditional lung segmentation algorithms struggle with juxtapleural nodules and imperfect lung segmentation.
  • Accurate segmentation is crucial for diagnosing lung nodules and tumors.

Purpose of the Study:

  • To propose a fully automatic method for lung parenchyma segmentation and repair.
  • To improve segmentation accuracy, especially for juxtapleural nodules and nodules adhering to the lung wall.

Main Methods:

  • Utilized optimal iterative threshold, 3D connectivity labeling, and 3D region growing for initial lung segmentation.
  • Employed improved chain code and Bresenham algorithms for lung parenchyma repair.
  • Compared the proposed method against the rolling-ball method using thoracic CT scans.

More Related Videos

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

Related Experiment Videos

Last Updated: May 17, 2026

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

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

Main Results:

  • Achieved 100% sensitivity for juxtapleural nodule inclusion.
  • Obtained 98.6% segmentation accuracy for juxtapleural nodule regions.
  • Demonstrated over 95.2% segmentation accuracy for lung parenchyma.
  • Average segmentation time of 0.67 seconds/frame.

Conclusions:

  • The proposed automatic method accurately segments lung parenchyma and repairs lung regions.
  • The algorithm effectively handles cases with nodules/tumors adhering to the lung wall.
  • This method offers a significant improvement over traditional techniques for lung nodule analysis.