The segmentation of cDNA microarray spots is essential in analyzing the intensities of microarray images for biological and medical investigation. In this work, nonparametric methods using kernel density estimation are applied to segment two-channel cDNA microarray images. This approach groups pixels into both a foreground and a background. The segmentation performance of this model is tested a...

Hepatocellular carcinoma (HCC) is one of the most common human malignancies in the world. To identify the histological subtype-specific genes of HCC, we analyzed the gene expression profile of 10 HCC patients by means of cDNA microarray. We proposed a systematic approach for determining the discriminatory genes and revealing the biological phenomena of HCC with cDNA microarray data. First, norm...

This paper presents a novel filtering framework capable of processing cDNA microarray images. The proposed two-component adaptive vector filters integrate well-known concepts from the areas of fuzzy set theory, nonlinear filtering, multidimensional scaling and robust order-statistics. By appropriately setting the weighting coefficients in a generalized framework, the method is capable of removi...

The microarray is an efficient device to analyze the expression level of many genes at once. cDNA microarrays are a promising technique for elucidating and interpreting the mechanistic roles of genes in the pathogenesis of patient’s tissues. However there has not been available cDNA microarrays that be able to analyze with small amount of RNA for each target-tissue. Moreover, the possibility of...

Several thousand genes can be monitored simultaneously using cDNA microarray technology. To exploit the huge amount of information contained in gene expression data, adaptation of existing and development of new computational methods are required. Recently, the Fuzzy C-Means (F-CM) method has been applied to cluster cDNA microarray data sets. To overcome some shortcomings of F-CM and to improve...

One of the most challenging tasks in microarray image analysis is spot segmentation. A solution to this problem is to provide an algorithm than can be used to find any spot within the microarray image. Circular Hough Transformation (CHT) is a powerful feature extraction technique used in image analysis, computer vision, and digital image processing. CHT algorithm is applied on the cDNA microarr...

OBJECTIVE To identify disease-specific gene expression profiles in patients with rheumatoid arthritis (RA), using complementary DNA (cDNA) microarray analyses on lymphoblastoid B cell lines (LCLs) derived from RA-discordant monozygotic (MZ) twins. METHODS The cDNA was prepared from LCLs derived from the peripheral blood of 11 pairs of RA-discordant MZ twins. The RA twin cDNA was labeled with ...

The complementary DNA (cDNA) sequence is considered to be the magic biometric technique for personal identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN). Microarray imaging is used for the concurrent identification of thousands of genes. We have segmented the location of the spots in a cDNA microarray. Thus, a precise localiza...

Multiple regions of the genome are often amplified during breast cancer development and progression, as evidenced in a number of published studies by comparative genomic hybridization (CGH). However, only relatively few target genes for such amplifications have been identified. Here, we indicate how small-scale commercially available cDNA and CGH microarray formats combined with the tissue micr...

BACKGROUND The molecular mechanisms underlying the progression of prostate cancer during hormonal therapy have remained poorly understood. In this study, we developed a new strategy for the identification of differentially expressed genes in hormone-refractory human prostate cancer by use of a combination of complementary DNA (cDNA) and tissue microarray technologies. METHODS Differences in g...