Lung Structure Classification Using 3D Geometric Measurements and SVM

  • João Rodrigo Ferreira da Silva Sousa
  • Aristófanes Corrêa Silva
  • Anselmo Cardoso de Paiva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)


In this paper, a set of three features for aiding classification of lung nodule bearing candidates based upon morphological characteristics is proposed. Metrics were validated using Support Vector Machine (SVM) technique as classifier. Preliminary results indicate the efficiency of the adopted measurements, taking into account the sensitivity and specificity high rates obtained from the studied samplings.


Lung Nodule Classification Geometric Measures SVM 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • João Rodrigo Ferreira da Silva Sousa
    • 1
  • Aristófanes Corrêa Silva
    • 1
  • Anselmo Cardoso de Paiva
    • 1
  1. 1.Federal University of Maranhão - UFMA, Av. dos Portugueses, SN, Campus do Bacanga, Bacanga, 65085-580, São Luís, MABrazil

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