Tsaftaris, Sotirios A. and Ahuja, Ramandeep and Shiell, Derek and Katsaggelos, Aggelos K. DNA microarray image intensity extraction using Eigenspots. In: International conference on image processing. IEEE, VI -265 . ISBN 978-1-4244-1437-6 (2007)Full text not available from this repository.
DNA microarrays are commonly used in the rapid analysis of gene expression in organisms. Image analysis is used to measure the average intensity of circular image areas (spots), which correspond to the level of expression of the genes. A crucial aspect of image analysis is the estimation of the background noise. Currently, background subtraction algorithms are used to estimate the local background noise and subtract it from the signal. In this paper we use principal component analysis (PCA) to de-correlate the signal from the noise, by projecting each spot on the space of eigenvectors, which we term eigenspots. PCA is well suited for such application due to the structural nature of the images. To compare the proposed method with other background estimation methods we use the industry standard signal-to-noise metric xdev.
|Item Type:||Book Section|
|Uncontrolled Keywords:||DNA microarray image intensity extraction; Principal Component Analysis; background subtraction algorithms; eigenspots; eigenvectors; image analysis;l ocal background noise; organisms; DNA; eigenvalues and eigenfunctions; image processing; medical image processing; principal component analysis|
|Subjects:||Q Science > QA Mathematics > QA76 Computer software
Q Science > QH Natural history > QH426 Genetics
|Research Area:||Computer Science and Applications|
|Depositing User:||Users 35 not found.|
|Date Deposited:||12 Aug 2011 10:23|
|Last Modified:||05 Mar 2013 15:47|
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