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3 July 1998 Computer-based objective quantitative assessment of pulmonary parenchyma via x-ray CT
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Abstract
This paper is a review of our recent studies using a texture- based tissue characterization method called the Adaptive Multiple Feature Method. This computerized method is automated and performs tissue classification based upon the training acquired on a set of representative examples. The AMFM has been applied to several different discrimination tasks including normal subjects, subjects with interstitial lung disease, smokers, asbestos-exposed subjects, and subjects with cystic fibrosis. The AMFM has also been applied to data acquired using different scanners and scanning protocols. The AMFM has shown to be successful and better than other existing techniques in discriminating the tissues under consideration. We demonstrate that the AMFM is considerably more sensitive and specific in characterizing the lung, especially in the presence of mixed pathology, as compared to more commonly used methods. Evidence is presented suggesting that the AMFM is highly sensitive to some of the earliest disease processes.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Renuka Uppaluri, Geoffrey McLennan M.D., Milan Sonka, and Eric A. Hoffman "Computer-based objective quantitative assessment of pulmonary parenchyma via x-ray CT", Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); https://doi.org/10.1117/12.312585
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