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Proceedings Paper

Importance of image quality for computing texture features in biomedical specimens
Author(s): Branko Palcic; Bruno Jaggi; Calum E. MacAulay
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Paper Abstract

Quantitative descriptions of features offer an objective cell classification. In addition, quantitative analysis is ideally suited for automated screening of samples for diseased (transformed) cells. More recently, it has been shown that subtle changes of DNA distribution in the nucleus can be detected by quantitative analysis which escape human detection . A key issue in quantitative analysis is the quality of the digital image which must be captured for such analysis . This paper focuses on the affect of image quality on the very important features--texture features--which have been shown to be the most powerful classifiers in quantitative pathology . Image quality affects these features in a direct and indirect way. The latter is the result of an effect on texture features by the segmentation process which in turn strongly depends on image quality.

Paper Details

Date Published: 1 August 1990
PDF: 8 pages
Proc. SPIE 1205, Bioimaging and Two-Dimensional Spectroscopy, (1 August 1990); doi: 10.1117/12.17791
Show Author Affiliations
Branko Palcic, B.C. Cancer Research Ctr. (Canada)
Bruno Jaggi, B.C. Cancer Research Ctr. (Canada)
Calum E. MacAulay, B.C. Cancer Research Ctr. (Canada)

Published in SPIE Proceedings Vol. 1205:
Bioimaging and Two-Dimensional Spectroscopy
Louis C. Smith, Editor(s)

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