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Related Concept Videos

Gross Anatomy of the Lungs01:17

Gross Anatomy of the Lungs

The lungs are a pair of vital organs connected to the trachea via the left and right bronchi. The base of these organs meets the dome-shaped muscle known as the diaphragm. Encased by the pleurae, the lungs contact the mediastinum. The right lung is shorter yet wider, and has a larger volume than the left lung. The left lung has an indentation known as the cardiac notch. The superior region of the lungs is referred to as the apex, whereas the base is the lower region near the diaphragm. The...

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Related Experiment Video

Updated: Jun 21, 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

Pulmonary lobe segmentation in CT examinations using implicit surface fitting.

Jiantao Pu1, Bin Zheng, Joseph K Leader

  • 1Imaging Research Division, Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA. puj@upmc.edu

IEEE Transactions on Medical Imaging
|July 25, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for segmenting lung lobes in 3D CT scans using implicit functions for fissures. The approach achieves high accuracy, especially with thinner slices, aiding diagnosis and treatment planning.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Computer-Aided Diagnosis

Background:

  • Accurate lung lobe segmentation in computed tomography (CT) is crucial for diagnosis and treatment planning.
  • Existing methods may struggle with incomplete fissure detection and require manual intervention.

Purpose of the Study:

  • To present a novel, automated scheme for segmenting lung lobes in 3D CT examinations.
  • To utilize implicit functions with Radial Basis Functions (RBFs) for robust fissure representation and natural lobe segmentation.

Main Methods:

  • Developed an automated scheme for lung lobe segmentation in 3D CT.
  • Represented pulmonary fissures using implicit functions with Radial Basis Functions (RBFs).
  • Employed a statistically based approach for fissure detection and greedy selection of constraint points for efficient surface fitting.

Main Results:

  • The automated scheme demonstrated high performance, with 50.8% of segmentations (0.625 mm slice thickness) rated "excellent" or "good" by radiologists.
  • Only 1.5% of segmentations were rated "poor" or "unacceptable."
  • Comparable results were observed with 1.25 mm slice thickness, while 2.5 mm slices showed performance degradation.

Conclusions:

  • The proposed automated scheme offers a reliable and efficient method for lung lobe segmentation in CT scans.
  • Its ability to handle incomplete fissures and its ease of implementation are significant advantages.
  • The method shows promise for improving diagnostic accuracy and treatment planning in thoracic imaging.