title: Automated identification of stained cells in tissue sections using digital image analysis.
abstract: OBJECTIVE
  To develop a novel automated image analysis system to differentiate immunohistochemically stained cells from background.
  
  
  METHODS
  Cell segmentation was performed by applying global thresholding algorithms to find an approximate threshold at which cells could be separated from background followed by a novel refinement algorithm to erode edge pixels of the region. To separate overlapping cells, a new decomposition method was developed that uses both semantic knowledge and high-level relational information. Both the cell segmentation and separation methods were evaluated on images of stained tissue sections and the manually outlined cell areas and numbers compared to the computed.
  
  
  RESULTS
  Macrophage areas computed at the first stage by Otsu's algorithm did not differ significantly (P = .07) from those traced manually, while the areas computed by Kittler's and Kurita's algorithms did not agree (P < .01). Both Otsu's and Kurita's algorithms performed well when combined with edge pixel erosion. Kittler's algorithm proved unsuccessful even with edge erosion. Comparison of the computed and manually determined cell numbers showed a significant correlation, and regression analysis resulted in the unity curve.
  
  
  CONCLUSIONS
  A combination of global thresholding and a novel edge erosion technique allowed identification of immunohistochemically stained macrophages; the computed cell areas agreed with the manual results.
authors.affiliation: Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic Foundation, Ohio, USA.
authors.forename: O
authors.initials: O
authors.lastname: Demirkaya
authors.forename: R M
authors.initials: RM
authors.lastname: Cothren
authors.forename: D G
authors.initials: DG
authors.lastname: Vince
authors.forename: J F
authors.initials: JF
authors.lastname: Cornhill
mesh_terms: D001011:Aorta / Q000166:cytology; D048429:Cell Size; D003331:Coronary Vessels / Q000166:cytology; D004056:Differential Threshold; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D007150:Immunohistochemistry; D008264:Macrophages / Q000166:cytology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013194:Staining and Labeling