Mining knowledge for HEp-2 cell image classification

Abe, 1994, Improvement of ELISA sensitivity by allogeneric adsorption of polyclonal antibodies: a technical note for non-experts, Clin. Chim. Acta, 224, 103, 10.1016/0009-8981(94)90126-0 Baird HS, Mallows CL. Bounded-error in pre-classification trees. In: Dori D, Bruckstein A, editors. Shape, structure and pattern recognition. Singapore: World Scientific, 1995, p. 100–10. Bradwell AR, Stokes RP, Johnson GD. Atlas of HEp-2 patterns. KNP Group Ltd., 1995. Cios KJ, Teresinska A, St. Konieczna, Potocka J, Sharma S. Diagnosing myocardial perfusion SPECT bull’s-eye maps: a knowledge discovery approach. IEEE Eng. Med. Biol. Mag. 19(4);17–25. Conrad K, Humbel R-L, Meurer M, Shoenfeld T, Tan EM. editors. Autoantigens and autoantibodies: diagnostic tools and clues to understanding autoimmunity. Berlin: Pabst Science Publisher, 2000. Garcia, 1999, The use of the Boolean model for texture analysis of gray images, Comput. Vision Image Understand., 74, 227, 10.1006/cviu.1999.0760 Matheron G. Random sets and integral geometry. New York: Wiley, 1975. Nakabayashi I, et al., Evaluation of the automatic fluorescent image analysis, image titer, for quantitative analysis of antinuclear antibodies. Am J Clin Pathol 2001:115. Online: http://www.ajcp.com/. Niemann H. Pattern analysis and understanding. Berlin (Heideberg): Springer, 1990. Otsu, 1979, A threshold selection method from gray level histograms, IEEE Trans. Syst. Man Cybernet., 9, 38, 10.1109/TSMC.1979.4310076 Perner P, Trautzsch S. Multi-interval discretization for decision tree learning. In: Amin A, Dori D, Pudil P, Freeman H, editors. Advances in pattern recognition, LNCS 1451. Berlin (Heidelberg): Springer, 1998. p. 475–82. Perner, 1994, A knowledge-based image inspection system for automatic defect recognition, classification, and process diagnosis, Int. J. Machine Vision Appl., 7, 135, 10.1007/BF01211659 Petrou M, Bosdogianni P. Image processing: the fundamentals. Chichester: Wiley, 1999. Quinlain, 1987, Simplifying decision tree, Int. J. Man-Machine Stud., 27, 221, 10.1016/S0020-7373(87)80053-6 Stoyan D, Kendall WS, Mecke J. Stochastic geometry and its applications. Berlin: Akademie Verlag, 1987. Weiss SM, Kulikowski CA. Computer systems that learn: classification and prediction methods from statistics, neural networks, machine learning, and expert systems. San Mateo: Morgan Kaufmann, 1990.