Complexity Aspects of Image Classification

  • Andreas A. Albrecht
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4987)


Feature selection and parameter settings for classifiers are both important issues in computer-assisted medical diagnosis. In the present paper, we highlight some of the complexity problems posed by both tasks. For the feature selection problem we propose a search-based procedure with a proven time bound for the convergence to optimum solutions. Interestingly, the time bound differs from fixed-parameter tractable algorithms by an instance-specific factor only. The stochastic search method has been utilized in the context of micro array data classification. For the classification of medical images we propose a generic upper bound for the size of classifiers that basically depends on the number of training samples only. The evaluation on a number of benchmark problems produced a close correspondence to the size of classifiers with best generalization results reported in the literature.


Feature Selection Focal Liver Lesion Circuit Complexity Feature Selection Problem Threshold Gate 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andreas A. Albrecht
    • 1
  1. 1.Science and Technology Research InstituteUniversity of HertfordshireHatfieldUK

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