title: Image processing for accurate cell recognition and count on histologic slides.
abstract: OBJECTIVE
  To design an automatic system for recognition and count of two different cell families on histologic slides.
  
  
  METHODS
  The segmentation strategy uses color information on the image. The morphologic operations and Support Vector Machine approaches are used for each color to obtain precise segmentation of the image into separate cells for recognition.
  
  
  RESULTS
  A large set of histologic slides of bone marrow was assessed byour system and the results compared to the score of a human expert. The results are in good agreement. The difference is within acceptable limits (below 10%).
  
  
  CONCLUSIONS
  The automatic system of cell recognition and extraction is accurate and provides a useful tool for cell recognition and count on histologic slides.
authors.affiliation: Warsaw University of Technology, Warsaw, Poland.
authors.forename: Tomasz
authors.initials: T
authors.lastname: Markiewicz
authors.forename: Stanislaw
authors.initials: S
authors.lastname: Osowski
authors.forename: Janusz
authors.initials: J
authors.lastname: Patera
authors.forename: Wojciech
authors.initials: W
authors.lastname: Kozlowski
mesh_terms: D002452:Cell Count / Q000379:methods*; D048430:Cell Shape; D002477:Cells / Q000166:cytology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity