Journal
RADIOLOGY
Volume 228, Issue 3, Pages 871-877Publisher
RADIOLOGICAL SOC NORTH AMERICA
DOI: 10.1148/radiol.2283020505
Keywords
bronchiolitis obliterans; computed tomography (CT), thin-section; computers, diagnostic aid; emphysema; lung, CT
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An automated technique for differentiation between a variety of obstructive lung diseases on the basis of textural analysis of thin-section computed tomographic (CT) images is described. From four regions of interest on each image, local texture information was extracted and represented by a 13-dimensional vector that contained statistical moments of the CT attenuation distribution, acquisition-length parameters, and cooccurrence descriptors. A supervised Bayesian classifier was used for texture feature segmentation. The technique was tested with a new cohort of subjects (n = 33, 660 regions of interest) with a similar spectrum of diseases. The proposed technique discriminates well between patterns of obstructive lung disease on the basis of parenchymal texture alone.
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