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Proceedings Paper

New image fusion method applied in two-wavelength detection of biochip spots
Author(s): Rang-Seng Chang; Jin-Yi Sheu; Ching-Huang Lin
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Paper Abstract

In the biological systems genetic information is read, stored, modified, transcribed and translated using the rule of molecular recognition. Every nucleic acid strand carries the capacity to recognize complementary sequences through base paring. Molecular biologists commonly use the DNA probes with known sequence to identify the unknown sequence through hybridization. There are many different detection methods for the hybridization results on a genechip. Fluorescent detection is a conventional method. The data analysis based on the fluorescent images and database establishment is necessary for treatment of such a large-amount obtained from a genechip. The unknown sequence has labeled with fluorescent material. Since the excitation and emission band is not a theoretical narrow band. There is a different in emission windows for different microscope. Therefore the data reading is different for different microscope. We combine two narrow band emission data and take it as two wavelengths from one fluorescence. Which by corresponding UV light excitation after we read the fluorescent intensity distribution of two microscope wavelengths for same hybridization DNA sequence spot, we will use image fusion technology to get best resultsDWe introduce a contrast and aberration correction image fusion method by using discrete wavelet transform to two wavelengths identification microarray biochip. This method includes two parts. First, the multiresolution analysis of the two input images are obtained by the discrete wavelet transform, from the ratio of high frequencies to the low frequency on the corresponding spatial resolution level, the directive contrast can be estimated by selecting the suitable subband signals of each input image. The fused image is reconstructed using the inverse wavelet transform.

Paper Details

Date Published: 18 September 2001
PDF: 9 pages
Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); doi: 10.1117/12.440306
Show Author Affiliations
Rang-Seng Chang, National Central Univ. (Taiwan)
Jin-Yi Sheu, Kwang Wu Institute of Technology (Taiwan)
Ching-Huang Lin, Hwa Hsia College of Technology and Commerce (Taiwan)


Published in SPIE Proceedings Vol. 4556:
Data Mining and Applications

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