Paper
5 September 2006 Enhancement of chest radiographs using eigenimage processing
Author Affiliations +
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philip J. Bones, Anthony P. H. Butler, and Michael Hurrell "Enhancement of chest radiographs using eigenimage processing", Proc. SPIE 6316, Image Reconstruction from Incomplete Data IV, 63160C (5 September 2006); https://doi.org/10.1117/12.683556
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image registration

Chest imaging

Image processing

Image classification

Diagnostics

Radiography

Principal component analysis

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