title: Clustering-based spot segmentation of cDNA microarray images.
abstract: Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.
authors.affiliation: Computer Engineering Department, Fatih University, B.Cekmece, Istanbul, Turkey. vuslan@fatih.edu.tr
authors.forename: Volkan
authors.initials: V
authors.lastname: Uslan
authors.forename: Ihsan Ömür
authors.initials: IÖ
authors.lastname: Bucak
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity