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Submitted to Image Anal Stereol, 8 pages Original Research Paper
 

Summary: Submitted to Image Anal Stereol, 8 pages
Original Research Paper
MORPHOLOGICAL MODEL-BASED MICROARRAY SPOT
CLASSIFICATION AND SEGMENTATION IN POLAR COORDINATES
JES ´US ANGULO
Centre de Morphologie Math´ematique, Mines de Paris, 35 rue Saint Honor´e, 77300 Fontainebleau, France
e-mail: jesus.angulo@ensmp.fr
(Submitted)
ABSTRACT
Robust image analysis of spots in microarrays (quality control + spot segmentation + quantification) is a
requirement for automated software which is of fundamental importance for a high-throughput analysis of
genomics microarray-based data. This paper deals with the development of model-based image processing
algorithms for qualifying/segmenting/quantifying adaptively each spot according its morphology. A series
of morphological models for the spot intensities are introduced. The spot categories represent most of
possible qualitative cases identified from a large database (different routines, techniques, etc.). Then based
on these spots models, a classification framework has been developed. The spot feature extraction and
classification (without segmenting) is based on converting the spot image to polar coordinates and, after
computing the radial/angular projections, the calculation of granulometric curves and derived parameters from
the projections. Spot contour segmentation can be solved by working in polar coordinates, and then calculating
the up/down minimal path, easily obtained with the generalized distance function. With this model-based

  

Source: Angulo,Jesús - Centre de Morphologie Mathématique, Ecole des Mines de Paris

 

Collections: Computer Technologies and Information Sciences