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Medical Knowledge Mining from Image Data : Synthesis of Medical Image Assessments for Early Stroke Detection

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The key issue of this study is synthesis of medical images and expert knowledge for early detection of a medical condition, such as stroke or cancer. Such synthesis is a missing link for making decisions during the diagnostic process. Knowledge mining in image databases can be enhanced by computing the relative importance of image features using pairwise comparisons. Computed weights can be systematically used for synthesis of various image features present in the same or different images.
Rocznik
Strony
283--298
Opis fizyczny
Bibliogr. 14 poz., il., wykr.
Twórcy
Bibliografia
  • [1] de Caritat, M. J. A. N., Marquis de Condorcet: Essai sur l'Application de L'Analyse à la Probabilité des Décisions Rendues à la Pluraliste des Voix, 1785. Facsimile reprint of original published in Paris, 1972, by the Imprimerie Royale.
  • [2] Fechner, G. T.: Elements of Psychophysics, Vol. 1. Translation by H. E. Adler of Elemente der Psychophysik (Leipzig Breitkopf und Hartel, 1860). Holt, Rinehart and Winston, New York, 1965.
  • [3] Thurstone, L. L., Law of Comparative Judgements, Psychological Review, 34, 273-286, 1927.
  • [4] Kato, T. (1992). Database architechture for content-based image retrieval. In Proceedings of the SPIE - The International Society for Optical Engineering, volume 1662 (pp. 112-113). San Jose, CA, USA.
  • [5] Koczkodaj, W. W., (1993), A New Definition of Consistency of Pairwise Comparisons. Mathematical and Computer Modelling, Vol. 18, 7, 79-84.
  • [6] Koczkodaj, W. W., (1996), Statistically Accurate Evidence of Improved Error Rate by Pairwise Comparisons. Perceptual and Motor Skills, 82, 43-48.
  • [7] Janicki, R., Koczkodaj, W. W., A Weak Order Solution to a Group Ranking and Consistency-driven Pairwise Comparisons, Applied Mathematics with Computation, 94(2/3), 227-236, 1998.
  • [8] Koczkodaj, W. W., Testing the Accuracy Enhancement of Pairwise Comparisons by a Monte Carlo Experiment, Journal of Statistical Planning and Inference, 69(1), 21-32, 1998.
  • [9] Kulikowski J. L., The role of ontological models in pattern recognition, Computer Recognition Systems. Proc. of the 4th International Conference on Computer Recognition Systems CORES'05 (M. Kurzynski et al eds), Springer, 43-52, 2005.
  • [13] Wardlaw J. M., Mielke O., Early signs of brain infarction at CT: observer reliability and outcome after thrornbolytic treatment - systematic review, Radiology 253(2), 444-453, 2005.
  • [10] Srinivasan A., Goyal M., Al Azri F., Lun C., State-of-the-art imaging of acute stroke, RadioGraphics 26, S75-S95, 2006.
  • [11] Muir K. W., Buchan A., von Kummer R., Rother J., Baron J. C., Imaging of acute stroke, Lancet Neurol 5, 755-768, 2006.
  • [12] Bozsóki, S., Rapcsák, T.. On Saaty's and Koczkodaj's inconsistencies of pairwise comparison matrices, Journal of Global Optimization, 42(2), 157-175, 2008.
  • [13] Koczkodaj, W. W., Robidoux, N., Tadeusiewicz, R., Classifing Visual Objects by the Consistency-driven Pairwise Comprisons Method, to appear in MG&V, 2009.
  • [14] Przelaskowski A., Ostrek G., Sklinda K., Wałecki J., Jozwiak R., Stroke slicer for CT-based automatic detection of acute ischemia, Advances in Intelligent and Soft Computing, Computer Recognition Systems, Springer 2009, in press
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA0-0048-0003
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