Robust automatic feature extraction for protein microarrays

Author

Ahmed, Murat O ; Dyer, Justin S ; Hytopoulos, Evangelos ; Itakura, Haruka ; Tsao, Philip S

Author_Institution

Dept. of Stat., Stanford Univ., Stanford, CA, USA

fYear

2009

fDate

5-7 May 2009

Firstpage

1773

Lastpage

1778

Abstract

In this paper, we present a robust methodology for image registration, segmentation, and feature extraction for protein microarrays. Originally designed for application to an Agilent microarray platform, the algorithms used are easily adapted to other platforms. Linear and nonlinear filtering techniques are used to identify protein signals on the array. After signal identification, expression values for each protein are then derived. Emphasis is placed on robustness of feature identification and low computational complexity.

Keywords

biological techniques; biology computing; computational complexity; feature extraction; image registration; image segmentation; molecular biophysics; proteins; Agilent microarray platform; computational complexity; image registration; image segmentation; linear filtering techniques; nonlinear filtering technique; protein microarrays; protein signal identification; robust automatic feature extraction; Algorithm design and analysis; Computational complexity; Feature extraction; Filtering; Image registration; Image segmentation; Nonlinear filters; Proteins; Robustness; Signal processing; Protein microarray; feature extraction; image processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2009. I2MTC '09. IEEE

Conference_Location

Singapore

ISSN

1091-5281

Print_ISBN

978-1-4244-3352-0

Type

conf

DOI

10.1109/IMTC.2009.5168744

Filename

5168744