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Related Experiment Video

Updated: Jun 1, 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

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

Adrien Depeursinge1, Alejandro Vargas, Frédéric Gaillard

  • 1MedGIFT Group, Business Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland. adrien.depeursinge@hevs.ch

International Journal of Computer Assisted Radiology and Surgery
|June 2, 2011
PubMed
Summary

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Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

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This study introduces a hybrid computer-aided diagnosis (CAD) system for interstitial lung diseases using high-resolution computed tomography. The system integrates image analysis and case retrieval, complementing traditional diagnostic workflows for improved clinical assessment.

Area of Science:

  • Radiology
  • Medical Imaging
  • Computer-Aided Diagnosis

Background:

  • Interstitial lung diseases (ILDs) pose diagnostic challenges.
  • High-resolution computed tomography (HRCT) is crucial for ILD assessment.
  • Current diagnostic workflows can be time-consuming and subjective.

Purpose of the Study:

  • To introduce and discuss clinical workflows and user interfaces for image-based computer-aided diagnosis (CAD) of ILDs.
  • To develop a system assisting students, radiologists, and physicians in ILD diagnosis workup.

Main Methods:

  • Implementation of three use cases for ILD diagnosis assistance.
  • Development of a system combining texture analysis for lung tissue pattern quantification.
  • Integration of content-based image retrieval (CBIR) and text-based search for similar case retrieval.

Related Experiment Videos

Last Updated: Jun 1, 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

Main Results:

  • A 3D map of categorized lung tissue patterns with disease quantification was generated.
  • A hybrid detection-CBIR-based CAD system was achieved, showing complementary roles.
  • Multimodal distance aggregation enabled efficient retrieval of similar cases based on imaging and clinical data.

Conclusions:

  • The developed system aligns with clinicians' traditional case-searching workflows.
  • It provides objective and customizable inter-case similarity assessment.
  • Leave-one-patient-out cross-validation demonstrated representative clinical utility.