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A new hardware architecture for performing the gridding of DNA microarray images

Published: 11 March 2007 Publication History

Abstract

DNA microarray technologies are an essential part of modern biomedical research. The analysis of DNA microarray images allows the identification of gene expressions in order to drawn biologically meaningful conclusions for applications that ranges from the genetic profiling to the diagnosis of oncology diseases. Unfortunately, DNA microarray technology has a high variation of data quality. Therefore, in order to obtain reliable results, complex and extensive image analysis algorithms should be applied before actual DNA microarray information can be used for biomedical purpose. In this paper, we present a novel hardware acceleration architecture specifically designed to process DNA microarray images. The proposed architecture uses several units working in a single instruction-multiple data fashion managed by a microprocessor core. An FPGA-based prototypal implementation of the developed architecture is presented. Experimental results on several realistic DNA microarray images show a reduction of the computation time of one order of magnitude if compared with previously developed software-based approach.

References

[1]
Amos Mosseri and Eitan Hirsh, "Analysis of Gene Expression Data," Lecture 3, Tel Aviv University, 2005.
[2]
Y.H. Yang, M.J. Buckley, S. Dudoit and T. P. Speed, "Comparison of Methods for Image Analysis on cDNA Microarray Data," Dept. Statistic, University of California at Berkeley, Tech. Rep. 584, Nov. 2000.
[3]
B. Fisher, S. Perkins, A. Walker, E. Wolfart, "Hypermedia Image Processing Reference," Department of Artificial Intelligence, University of Edinburg, available on http://www.cee.hw.uk
[4]
P. Bajcsy, "An overview of DNA Microarray Image Requirements for Automated Processing," IEEE Conference on Computer Vision and Pattern Recognition, vol. 3, pp. 147, 2005.
[5]
Yuan-Kai Wang and Cheng-Wei Huang, "DNA Microarray Image Analysis Using Active Control Model", IEEE Computational Systems Bioinformatics Conference, pp. 12--13, 2005.
[6]
P. Bajcsy, "Gridline: Automatic grid alignment DNA microarray scans," IEEE Transactions on Image Processing, vol. 13, issue 1, pp. 15--25, Jan 2004.
[7]
X. H. Wang, Robert S. H. Istepanian and Yong Hua Song, "Microarray Image Enhancement Denoising Using Stationary Wavelet Transform," IEEE Transactions on Nanobioscience, vol. 2, issue 4, pp. 184--190, Dec. 2003.
[8]
S. Samavi, S. Shirani, N. Karimi, M. Jamal Deen, "A Pipeline Architecture for Processing of DNA Microarrays Images," Ed. Springer Journal of VLSI Signal Processing, Vol. 38, No. 3, pp. 287--297, November 2004.
[9]
Standford University, "Stanford Microarray Database," Available: http://smd.stanford.edu/
[10]
J. F. Canny, "A computational approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6): 769--798, November 1986.
[11]
Xilinx Product Specification, "Virtex-II Pro and Virtex-II Pro X Platform FPGAs: Complete Data Sheets," DS084 v4.5, October 10, 2005.
[12]
Xilinx Reference Guide, "PowerPC Processor," EDK 6.1, September 2, 2003.

Cited By

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  • (2018)A soft multi-core architecture for edge detection and data analysis of microarray imagesJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2009.11.00456:1(48-62)Online publication date: 29-Dec-2018
  • (2018)Real-time lossless compression of microarray images by separate compaction of foreground and backgroundComputer Standards & Interfaces10.1016/j.csi.2014.12.00139:C(34-43)Online publication date: 28-Dec-2018

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  1. A new hardware architecture for performing the gridding of DNA microarray images

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        cover image ACM Conferences
        GLSVLSI '07: Proceedings of the 17th ACM Great Lakes symposium on VLSI
        March 2007
        626 pages
        ISBN:9781595936059
        DOI:10.1145/1228784
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        Published: 11 March 2007

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        Author Tags

        1. DNA microarray
        2. FPGA
        3. edge detection
        4. image data-processing

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        March 11 - 13, 2007
        Stresa-Lago Maggiore, Italy

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        Overall Acceptance Rate 312 of 1,156 submissions, 27%

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        • (2018)A soft multi-core architecture for edge detection and data analysis of microarray imagesJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2009.11.00456:1(48-62)Online publication date: 29-Dec-2018
        • (2018)Real-time lossless compression of microarray images by separate compaction of foreground and backgroundComputer Standards & Interfaces10.1016/j.csi.2014.12.00139:C(34-43)Online publication date: 28-Dec-2018

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