DNA microarray image intensity extraction using eigenspots

Sotirios A. Tsaftaris*, Ramandeep Ahuja, Derek Shiell, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2007 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-7
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3061-3064
Number of pages4
ISBN (Print)978-1-4244-1436-9
Publication statusPublished - 2007
EventIEEE International Conference on Image Processing (ICIP 2007) - San Antonio, United Kingdom
Duration: 16 Sep 200719 Sep 2007

Publication series

NameIEEE International Conference on Image Processing ICIP
PublisherIEEE
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing (ICIP 2007)
CountryUnited Kingdom
Period16/09/0719/09/07

Keywords

  • DNA microarray
  • biochip
  • eigenspaces
  • noise
  • segmentation

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