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Obstructive Lung Diseases: Texture Classification for Differentiation at CT¹

¹ From the Department of Visual Information Processing (F.C., G.Z.Y.) and Division of Investigative Sciences (D.M.H.), Imperial College of Science, Technology and Medicine, Royal Brompton Hospital, Sydney St, London SW3 6NP, England. Received April 30, 2002; revision requested July 10; final revision received December 19; accepted January 13, 2003. F.C. supported by Imatron, San Francisco, Calif. Address correspondence to D.M.H. (e-mail: d.hansell@rbh.nthames.nhs.uk).

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 co-occurrence 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.

© RSNA, 2003

Index terms: Bronchiolitis obliterans, 60.219 • Computed tomography (CT), thin-section, 60.12115 • Computers, diagnostic aid, 60.12115 • Emphysema, 60.7512, 60.7513 • Lung, CT, 60.12115

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