Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/15870
Title: Microarray image analysis
Researcher: Manjunath, S S
Guide(s): Lalitha Rangarajan
Keywords: Computer Science
Microarray image
Upload Date: 14-Feb-2014
University: University of Mysore
Completed Date: 2012
Abstract: Microarray is an important tool and powerful technique that is used to analyse the expression of DNA in organisms for large scale gene sequences and gene expressions. Microarray technology allows massively parallel, high throughput profiling of gene expression in a single hybridization experiment. Processing of microarray images provides the input for further analysis of the extracted microarray data. It includes the following stages: and#61623; Gridding is the process of identifying the area within an image that contain a single spot, subgrid and row, column within that subgrid. Segmentation is the process of grouping the pixels in a spot with similar features (this step results in the separation of foreground and background pixels). Intensity extraction calculates red and green foreground fluorescence intensity pairs. Preprocessing A major factor that complicates the task of image analysis and data mining is that microarray experiments involve a number of error-prone steps (occurring during fabrication, target labeling and hybridization), which induce noise on the resulting images. Microarray images are also corrupted by irregularities in the shape, size, and position of the spot. Most of the methods proposed by researchers have either considered high SNR (signal-to-noise ratio) images or various assumptions on factors such as type of thresholding used, parametric assumptions and decomposition levels. Also, some of the methods have discussed only impulse, Gaussian noise and fluorescent noise. In this research work, methods are developed, for low SNR images and estimate many other types of noises other than Gaussian, impulse and fluorescent noises. Denoising of microarray image is an essential and challenging task in the pre-processing step of microarray image analysis. newlineHere, we have proposed two novel techniques for image restoration.
Pagination: 179p.
URI: http://hdl.handle.net/10603/15870
Appears in Departments:Department of Computer Science

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02_certificate.pdf99.9 kBAdobe PDFView/Open
03_declaration.pdf99.01 kBAdobe PDFView/Open
04_acknowledgements.pdf19.13 kBAdobe PDFView/Open
05_dedication.pdf27.54 kBAdobe PDFView/Open
06_abstract.pdf119.79 kBAdobe PDFView/Open
07_list of figures.pdf177.83 kBAdobe PDFView/Open
08_list of tables.pdf161.85 kBAdobe PDFView/Open
09_contents.pdf140.7 kBAdobe PDFView/Open
10_chapter 1.pdf349.17 kBAdobe PDFView/Open
11_chapter 2.pdf255.47 kBAdobe PDFView/Open
12_chapter 3.pdf1.27 MBAdobe PDFView/Open
13_chapter 4.pdf1.32 MBAdobe PDFView/Open
14_chapter 5.pdf529.98 kBAdobe PDFView/Open
15_chapter 6.pdf2.41 MBAdobe PDFView/Open
16_chapter 7.pdf203.04 kBAdobe PDFView/Open
17_bibliography.pdf194.86 kBAdobe PDFView/Open


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