Computer-assisted detection of infectious lung diseases: A review

نویسندگان

  • Ulas Bagci
  • Mike Bray
  • Jesus Caban
  • Jianhua Yao
  • Daniel J. Mollura
چکیده

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.

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عنوان ژورنال:
  • Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

دوره 36 1  شماره 

صفحات  -

تاریخ انتشار 2012