DNA Modeling in Biomedical Image Matching

Mohammad Reza Dawoudi
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Mohammad Reza Dawoudi: Tampere University of Technology, Finland

Current Trends in Biomedical Engineering & Biosciences, 2017, vol. 8, issue 4, 96-99

Abstract: Medical image matching (MIM) is the application of image processing techniques to clinical diagnosis. In this work a novel method for the alignment of different MRI images is evaluated. This method called as The Quarter Code Algorithm. The method is based on the linear mapping and the one-to-one correspondences between point features extracted from the images and on calculating similarities in pixel values. This correspondence is determined by comparing two strings constructed from pixel values of the images. The method uses a table called the Quarter Code table, which is the set of characters and numbers. In this table every number between 0 and 255 is translated into a unique string of four letter alphabet. Letters A, C, G, T are chosen, since they are the same as used in DNA sequences. In this way it possible to utilize tools originally programmed to DNA sequences analysis. When all pixel values of MRI images are converted to virtual DNA sequences, one can show the differences between two virtual DNA sequences. The comparison between two virtual DNA sequences is done by Chi-squared test, Markov Chain and glm plot.

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Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jctbeb:v:8:y:2017:i:4:p:96-99

DOI: 10.19080/CTBEB.2017.08.555744

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