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 if 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.
Keywords
- Lung Parenchyma
- High Resolution Compute Tomographic
- Obliterative Bronchiolitis
- Wavelet Feature
- Small Airway Disease
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1997 Springer-Verlag Berlin Heidelberg
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Yang, GZ., Hansell, D.M. (1997). A hybrid approach for the detection of small airways disease from Computed Tomographic images. In: Duncan, J., Gindi, G. (eds) Information Processing in Medical Imaging. IPMI 1997. Lecture Notes in Computer Science, vol 1230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63046-5_41
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DOI: https://doi.org/10.1007/3-540-63046-5_41
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Online ISBN: 978-3-540-69070-2
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