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A Multiple Kernel Learning Algorithm for Cell Nucleus Classification of Renal Cell Carcinoma

  • Peter Schüffler
  • Aydın Ulaş
  • Umberto Castellani
  • Vittorio Murino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6978)

Abstract

We consider a Multiple Kernel Learning (MKL) framework for nuclei classification in tissue microarray images of renal cell carcinoma. Several features are extracted from the automatically segmented nuclei and MKL is applied for classification. We compare our results with an incremental version of MKL, support vector machines with single kernel (SVM) and voting. We demonstrate that MKL inherently combines information from different input spaces and creates statistically significantly more accurate classifiers than SVMs and voting for renal cell carcinoma detection.

Keywords

MKL renal cell carcinoma SVM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Peter Schüffler
    • 1
  • Aydın Ulaş
    • 2
  • Umberto Castellani
    • 2
  • Vittorio Murino
    • 2
    • 3
  1. 1.Department of Computer ScienceETH ZürichZürichSwitzerland
  2. 2.Department of Computer ScienceUniversity of VeronaVeronaItaly
  3. 3.Istituto Italiano di Tecnologia (IIT)GenovaItaly

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