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Proceedings Paper

Enhancement of chest radiographs using eigenimage processing
Author(s): Philip J. Bones; Anthony P. H. Butler; Michael Hurrell
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Paper Abstract

Frontal chest radiographs ("chest X-rays") are routinely used by medical personnel to assess patients for a wide range of suspected disorders. Often large numbers of images need to be analyzed. Furthermore, at times the images need to analyzed ("reported") when no radiological expert is available. A system which enhances the images in such a way that abnormalities are more obvious is likely to reduce the chance that an abnormality goes unnoticed. The authors previously reported the use of principal components analysis to derive a basis set of eigenimages from a training set made up of images from normal subjects. The work is here extended to investigate how best to emphasize the abnormalities in chest radiographs. Results are also reported for various forms of image normalizing transformations used in performing the eigenimage processing.

Paper Details

Date Published: 5 September 2006
PDF: 12 pages
Proc. SPIE 6316, Image Reconstruction from Incomplete Data IV, 63160C (5 September 2006); doi: 10.1117/12.683556
Show Author Affiliations
Philip J. Bones, Univ. of Canterbury (New Zealand)
Anthony P. H. Butler, Univ. of Canterbury (New Zealand)
Michael Hurrell, Christchurch Hospital (New Zealand)


Published in SPIE Proceedings Vol. 6316:
Image Reconstruction from Incomplete Data IV
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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