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8 April 1996 Texture analysis of pulmonary parenchyma in normal and emphysematous lung
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Abstract
Tissue characterization using texture analysis is gaining increasing importance in medical imaging. We present a completely automated method for discriminating between normal and emphysematous regions from CT images. This method involves extracting seventeen features which are based on statistical, hybrid and fractal texture models. The best subset of features is derived from the training set using the divergence technique. A minimum distance classifier is used to classify the samples into one of the two classes--normal and emphysema. Sensitivity and specificity and accuracy values achieved were 80% or greater in most cases proving that texture analysis holds great promise in identifying emphysema.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Renuka Uppaluri, Theophano Mitsa, Eric A. Hoffman, Geoffrey McLennan M.D., and Milan Sonka "Texture analysis of pulmonary parenchyma in normal and emphysematous lung", Proc. SPIE 2709, Medical Imaging 1996: Physiology and Function from Multidimensional Images, (8 April 1996); https://doi.org/10.1117/12.237888
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