DocumentCode :
1506229
Title :
3-D Spot Modeling for Automatic Segmentation of cDNA Microarray Images
Author :
Zacharia, Eleni ; Maroulis, Dimitris
Author_Institution :
Dept. of Inf. & Telecommun., Univ. of Athens, Ilisia, Greece
Volume :
9
Issue :
3
fYear :
2010
Firstpage :
181
Lastpage :
192
Abstract :
Spot segmentation-the second essential stage of cDNA microarray image analysis-constitutes a challenging process. At present, several up-to-date spot-segmentation techniques or software programs-proposed in the literature-are often characterized as “automatic.” On the contrary, they are in effect not fully automatic since they require human intervention in order to specify mandatory input parameters or to correct their results. Human intervention, however, can inevitably modify the actual results of the cDNA microarray experiment and lead to erroneous biological conclusions. Therefore, the development of an automated spot-segmentation process becomes of exceptional interest. In this paper, an original and fully automatic approach to accurately segmenting the spots in a cDNA microarray image is presented. In order for the segmentation to be accomplished, each real spot of the cDNA microarray image is represented in a three-dimensional (3-D) space by a 3-D spot model. Each 3-D spot model is determined via an optimization problem, which is solved by using a genetic algorithm. The segmentation of real spots is conducted by drawing the contours of their 3-D spot models. The proposed method has been compared with various published and established techniques, using several synthetic and real cDNA microarray images that contain thousands of spots. The outcome has shown that the proposed method outperforms prevalent existing techniques. It is also noise resistant and yields excellent results even under adverse conditions such as the appearance of spots of various sizes and shapes.
Keywords :
DNA; biological techniques; edge detection; genetic algorithms; image segmentation; molecular biophysics; 3D spot model contour; 3D spot modeling; automated spot segmentation process; cDNA microarray images; genetic algorithm; optimization problem; 3-D spot modeling; cDNA microarrays; genetic algorithm; image analysis; spot segmentation; Algorithms; Fuzzy Logic; Gene Expression Profiling; Humans; Imaging, Three-Dimensional; Models, Genetic; Oligonucleotide Array Sequence Analysis; Precursor Cell Lymphoblastic Leukemia-Lymphoma;
fLanguage :
English
Journal_Title :
NanoBioscience, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1241
Type :
jour
DOI :
10.1109/TNB.2010.2050900
Filename :
5475215
Link To Document :
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