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Australas Phys Eng Sci Med ; 36(4): 449-55, 2013 Dec.
Article in English | MEDLINE | ID: mdl-24104449

ABSTRACT

Previous work has investigated the feasibility of using Eigenimage-based enhancement tools to highlight abnormalities on chest X-rays (Butler et al in J Med Imaging Radiat Oncol 52:244-253, 2008). While promising, this approach has been limited by computational restrictions of standard clinical workstations, and uncertainty regarding what constitutes an adequate sample size. This paper suggests an alternative mathematical model to the above referenced singular value decomposition method, which can significantly reduce both the required sample size and the time needed to perform analysis. Using this approach images can be efficiently separated into normal and abnormal parts, with the potential for rapid highlighting of pathology.


Subject(s)
Algorithms , Radiographic Image Enhancement , Humans , Lung Neoplasms/diagnostic imaging , Pneumonia/diagnostic imaging , Radiography, Thoracic , X-Rays
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