title: Computer-assisted detection of infectious lung diseases: a review.
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.
authors: Center for Infectious Disease Imaging, Department of Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, MD 20892, USA. ulasbagci@gmail.com
authors: Ulaş
authors: U
authors: Bağcı
authors: Mike
authors: M
authors: Bray
authors: Jesus
authors: J
authors: Caban
authors: Jianhua
authors: J
authors: Yao
authors: Daniel J
authors: DJ
authors: Mollura
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging*; D008171:Lung Diseases / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012141:Respiratory Tract Infections / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*