Classification Algorithms for Biomedical Volume Datasets

  • Jesús Cerquides
  • Maite López-Sánchez
  • Santi Ontañón
  • Eloi Puertas
  • Anna Puig
  • Oriol Pujol
  • Dani Tost
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4177)

Abstract

This paper analyzes how to introduce machine learning algorithms into the process of direct volume rendering. A conceptual framework for the optical property function elicitation process is proposed and particularized for the use of attribute-value classifiers. The process is evaluated in terms of accuracy and speed using four different off-the-shelf classifiers (J48, Naïve Bayes, Simple Logistic and ECOC-Adaboost). The empirical results confirm the classification of biomedical datasets as a tough problem where an opportunity for further research emerges.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jesús Cerquides
    • 1
  • Maite López-Sánchez
    • 1
  • Santi Ontañón
    • 1
  • Eloi Puertas
    • 1
    • 2
  • Anna Puig
    • 1
  • Oriol Pujol
    • 1
  • Dani Tost
    • 3
  1. 1.Dept. MAiA, UBWAI: Volume Visualization and Artificial Intelligence Group 
  2. 2.IIIA: Institut d’Investigació en Intel ligència ArtificialCSIC 
  3. 3.CREB: Centre de Recerca en Enginyeria BiomèdicaUPC 

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