IDEAS home Printed from https://ideas.repec.org/a/adp/jctbeb/v8y2017i4p96-99.html
   My bibliography  Save this article

DNA Modeling in Biomedical Image Matching

Author

Listed:
  • Mohammad Reza Dawoudi

    (Tampere University of Technology, Finland)

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.

Suggested Citation

  • Mohammad Reza Dawoudi, 2017. "DNA Modeling in Biomedical Image Matching," Current Trends in Biomedical Engineering & Biosciences, Juniper Publishers Inc., vol. 8(4), pages 96-99, August.
  • Handle: RePEc:adp:jctbeb:v:8:y:2017:i:4:p:96-99
    DOI: 10.19080/CTBEB.2017.08.555744
    as

    Download full text from publisher

    File URL: https://juniperpublishers.com/ctbeb/pdf/CTBEB.MS.ID.555744.pdf
    Download Restriction: no

    File URL: https://juniperpublishers.com/ctbeb/CTBEB.MS.ID.555744.php
    Download Restriction: no

    File URL: https://libkey.io/10.19080/CTBEB.2017.08.555744?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Loet Leydesdorff & Liwen Vaughan, 2006. "Co‐occurrence matrices and their applications in information science: Extending ACA to the Web environment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(12), pages 1616-1628, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    2. Jia Feng & Yun Qiu Zhang & Hao Zhang, 2017. "Improving the co-word analysis method based on semantic distance," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1521-1531, June.
    3. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Jesper W. Schneider & Birger Larsen & Peter Ingwersen, 2009. "A comparative study of first and all-author co-citation counting, and two different matrix generation approaches applied for author co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 103-130, July.
    5. van Eck, N.J.P. & Waltman, L., 2007. "Appropriate Similarity Measures for Author Cocitation Analysis," ERIM Report Series Research in Management ERS-2007-091-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Jimi Adams & Ryan Light, 2014. "Mapping Interdisciplinary Fields: Efficiencies, Gaps and Redundancies in HIV/AIDS Research," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-13, December.
    7. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    8. Georg Groh & Christoph Fuchs, 2011. "Multi-modal social networks for modeling scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 569-590, November.
    9. Wei-Feng Tung & Ting-Yu Lee, 2013. "Rank-mediated collaborative tagging recommendation service using video-tag relationship prediction," Information Systems Frontiers, Springer, vol. 15(4), pages 627-635, September.
    10. Hao Wang & Sanhong Deng & Xinning Su, 2016. "A study on construction and analysis of discipline knowledge structure of Chinese LIS based on CSSCI," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1725-1759, December.
    11. Yang Li & Frank Neffke, 2022. "Relatedness in regional development: in search of the right specification," Papers in Evolutionary Economic Geography (PEEG) 2208, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Apr 2022.
    12. Carlos Sánchez‐Camacho & Rocío Carranza & David Martín‐Consuegra & Estrella Díaz, 2022. "Evolution, trends and future research lines in corporate social responsibility and tourism: A bibliometric analysis and science mapping," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(3), pages 462-476, June.
    13. Shakibian, Hadi & Charkari, Nasrollah Moghadam, 2018. "Statistical similarity measures for link prediction in heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 248-263.
    14. Zhao, Dangzhi & Strotmann, Andreas, 2008. "Comparing all-author and first-author co-citation analyses of information science," Journal of Informetrics, Elsevier, vol. 2(3), pages 229-239.
    15. Gregorio González-Alcaide & Pedro Llorente & José M. Ramos, 2016. "Bibliometric indicators to identify emerging research fields: publications on mass gatherings," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1283-1298, November.
    16. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
    17. Lola García-Santiago & Felix Moya-Anegón, 2009. "Using co-outlinks to mine heterogeneous networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(3), pages 681-702, June.
    18. Guangtong Li & L. Siddharth & Jianxi Luo, 2023. "Embedding knowledge graph of patent metadata to measure knowledge proximity," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(4), pages 476-490, April.
    19. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    20. Wolfram, Dietmar & Zhao, Yuehua, 2014. "A comparison of journal similarity across six disciplines using citing discipline analysis," Journal of Informetrics, Elsevier, vol. 8(4), pages 840-853.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:adp:jctbeb:v:8:y:2017:i:4:p:96-99. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robert Thomas (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.