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Leukocyte Detection Using Nucleus Contour Propagation

  • Daniela M. Ushizima
  • Rodrigo T. Calado
  • Edgar G. Rizzatti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4091)

Abstract

We propose a new technique for medical image segmentation, focused on front propagation in blood smear images to fully automate leukocyte detection. The current approach also incorporates contextual information, which it is especially important in direct general algorithms to the applied problem. A Bayesian classification of pixels is used to estimate cytoplasm color and is embedded in the speed function to accomplish cytoplasm boundary estimation. We report encouraging results, with evaluations considering difficult situations as cell adjacency and filamentous cytoplasmic projections.

Keywords

Front Propagation Hairy Cell Speed Function Computational Pipeline Medical Image Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Daniela M. Ushizima
    • 1
  • Rodrigo T. Calado
    • 2
  • Edgar G. Rizzatti
    • 2
  1. 1.Inteligent System GroupCatholic University of Santos 
  2. 2.College of MedicineUniversity of Sao Paulo 

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