2010
DOI: 10.1504/ijcbdd.2010.035237
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A multi-view approach to cDNA micro-array analysis

Abstract: Microarray has emerged as a powerful technology that enables biologists to study thousands of genes simultaneously, therefore, to obtain a better understanding of the gene interaction and regulation mechanisms. This paper is concerned with improving the processes involved in the analysis of microarray image data. The main focus is to clarify an image's feature space in an unsupervised manner. In this paper, the Image Transformation Engine (ITE), combined with different filters, is investigated. The proposed me… Show more

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Cited by 5 publications
(6 citation statements)
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“…For this purpose, an image quality measurement, known as the peak signal-to-noise ratio (PSNR) [32], is used and the rational is justified as follows.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…For this purpose, an image quality measurement, known as the peak signal-to-noise ratio (PSNR) [32], is used and the rational is justified as follows.…”
Section: Discussionmentioning
confidence: 99%
“…The higher the PSNR value the more strongly the binary spot mask fits with the raw image surface. The PSNR is a much better measure of the suitability of a spot mask to the raw image area containing the spot as it is more resilient against large intensity ranges within the spot area compared to the MSE [32]. Fig.…”
Section: Discussionmentioning
confidence: 99%
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“…In this part, a well-defined quality criterion called the peak signal-to-noise ratio (PSNR) [36] is exploited to quantify the segmentation performance of DBN method for GICS images, and also verify the effectiveness of the test and control lines in this study. In general, the PSNR is viewed as a measurement of peak error.…”
Section: Quantitative Evaluationmentioning
confidence: 99%
“…As an important performance indicator, the PSNR describes the ratio of the signal's peak value over the magnitude of the background noise. Generally, we prefer a larger PSNR value since the binary spot mask in this way fits better with the raw image surface [36]. Fig.…”
Section: Quantitative Evaluationmentioning
confidence: 99%