Detection of Pathological Cells in Phase Contrast Cytological Images

  • Marcin Smereka
  • Grzegorz Glab
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)


This paper presents a practical combination of image processing and pattern recognition techniques in order to identify pathological and atypical cells in phase contrast cytological images. The algorithms involved in the processing cover: oriented edge detection, ridge following, contour grouping and ellipse fitting. The Hough Transform and other techniques are discussed for comparison. Various pattern recognition techniques are tested and compared. All the exploited algorithms were customized to reflect specificity of phase contrast images and apriori–knowledge of cytological smear. Possible applications of this algorithm for automated screening systems are enumerated.


Active Contour Hough Transform Pattern Recognition Technique Pathological Cell Edge Segment 
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

  • Marcin Smereka
    • 1
  • Grzegorz Glab
    • 2
  1. 1.Institute of Computer Engineering, Control & RoboticsWroclaw University of TechnologyWroclawPoland
  2. 2.Gynecological Clinic GMWOpolePoland

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