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Proceedings Paper

Automatic assessment of small airways disease with computed tomography
Author(s): Guang-Zhong Yang; Michael Rubens; David M. Hansell
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Paper Abstract

Bronchiolar obstruction is commonly manifested in computed tomographic (CT) images as areas of decreased attenuation relative to adjacent normal lung parenchyma. The certain identification of such areas is difficult in practice, particularly is such areas are poorly marginated. This paper presents a novel approach to the enhancement of feature differences between normal and diseased lung parenchyma so that reliable visual assessment can be made. The method relies on a hybrid structural filtering technique which removes pulmonary vessels appearing in the CT cross- sectional images without affecting intrinsic subtle intensity details of the lung parenchyma. In order to restore possible structural distortions introduced by the hybrid filter, a feature localization process based on wavelet reconstruction of feature extrema is used. After contrast enhancement the resultant images are used to delineate region borders of the diseased areas and quantification is made with regard to the extent of the disease. Clinically, the proposed technique is especially valuable for presymptomatic cases in which direct visual assessment of the unprocessed images by different observers often yields inconsistent results.

Paper Details

Date Published: 9 May 1997
PDF: 11 pages
Proc. SPIE 3033, Medical Imaging 1997: Physiology and Function from Multidimensional Images, (9 May 1997); doi: 10.1117/12.274030
Show Author Affiliations
Guang-Zhong Yang, Royal Brompton Hospital (United Kingdom)
Michael Rubens, Royal Brompton Hospital (United Kingdom)
David M. Hansell, Royal Brompton Hospital (United Kingdom)

Published in SPIE Proceedings Vol. 3033:
Medical Imaging 1997: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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