Authors:
Peter Peer
1
and
Luis Galo Corzo
2
Affiliations:
1
CEIT and Tecnun (University of Navarra); Faculty of Computer and Information Science, University of Ljubljana, Slovenia
;
2
CEIT and Tecnun (University of Navarra); Asiris Vision Technologies, Spain
Keyword(s):
Image analysis, two-dimensional gel electrophoresis, segmentation.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Two-dimensional gel electrophoresis (2-DE) images show the expression levels of several hundred of proteins where each protein is represented as a blob shaped spot of grey level values. The spot detection, i.e. segmentation process has to be efficient as it is the first step in the gel processing. Such extraction of information is a very complex task. In this paper we propose a real time spot detector that is basically a morphology based method with use of seeded region growing as a central paradigm and which relies on the spot correlation information. The method is tested on gels with human samples in SWISS-2DPAGE (two-dimensional polyacrylamide gel electrophoresis) database. The average time to process the image is less than a second, while the results are very intuitive for human perception and as such they help the user to focus on important parts of the gel in the subsequent processing. In gels with less than 50 identified spots as proteins (proteins that compose a proteome) in
the mentioned database, the algorithm detects all obvious spots.
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