Computer-assisted detection of infectious lung diseases: A review

Ulaş Baĝci*, Mike Bray, Jesus Caban, Jianhua Yao, Daniel J. Mollura

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

61 Scopus citations

Abstract

Respiratory tract infections are a leading cause of death and disability worldwide. Although radiology serves as a primary diagnostic method for assessing respiratory tract infections, visual analysis of chest radiographs and computed tomography (CT) scans is restricted by low specificity for causal infectious organisms and a limited capacity to assess severity and predict patient outcomes. These limitations suggest that computer-assisted detection (CAD) could make a valuable contribution to the management of respiratory tract infections by assisting in the early recognition of pulmonary parenchymal lesions, providing quantitative measures of disease severity and assessing the response to therapy. In this paper, we review the most common radiographic and CT features of respiratory tract infections, discuss the challenges of defining and measuring these disorders with CAD, and propose some strategies to address these challenges.

Original languageEnglish (US)
Pages (from-to)72-84
Number of pages13
JournalComputerized Medical Imaging and Graphics
Volume36
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

Keywords

  • Computer assisted detection
  • Feature extraction
  • Infectious diseases
  • Lung CT
  • Texture analysis
  • Tomography

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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