DNA microarray image intensity extraction using eigenspots

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

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 (US)
Title of host publication2007 IEEE International Conference on Image Processing, ICIP 2007 Proceedings
DOIs
StatePublished - Dec 1 2006
Event14th IEEE International Conference on Image Processing, ICIP 2007 - San Antonio, TX, United States
Duration: Sep 16 2007Sep 19 2007

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume6
ISSN (Print)1522-4880

Other

Other14th IEEE International Conference on Image Processing, ICIP 2007
CountryUnited States
CitySan Antonio, TX
Period9/16/079/19/07

Keywords

  • Biochip
  • DNA microarray
  • Eigenspaces
  • Noise
  • Segmentation

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'DNA microarray image intensity extraction using eigenspots'. Together they form a unique fingerprint.

Cite this