title: Computer approach to recognition of Fuhrman grade of cells in clear-cell renal cell carcinoma.
abstract: OBJECTIVE
  To present a computerized system for recognition of Fuhrman grade of cells in clear-cell renal cell carcinoma on the basis of microscopic images of the neoplasm cells in application of hematoxylin and eosin staining.
  
  
  METHODS
  The applied methods use combined gradient and mathematical morphology to obtain nuclei and classifiers in the form of support vector machine to estimate their Fuhrman grade. The starting point is a microscopic kidney image, which is subject to the advanced methods of preprocessing, leading finally to estimation of Fuhrman grade of cells and the whole analyzed image.
  
  
  RESULTS
  The results of the numerical experiments have shown that the proposed nuclei descriptors based on different principles of generation are well connected with the Fuhrman grade. These descriptors have been used as the diagnostic features forming the inputs to the classifier, which performs the final recognition of the cells. The average discrepancy rate between the score of our system and the human expert results, estimated on the basis of over 3,000 nuclei, is below 10%.
  
  
  CONCLUSIONS
  The obtained results have shown that the system is able to recognize 4 Fuhrman grades of the cells with high statistical accuracy and agreement with different expert scores. This result gives a good perspective to apply the system for supporting and accelerating the research of kidney cancer.
authors.forename: Michal
authors.initials: M
authors.lastname: Kruk
authors.forename: Stanislaw
authors.initials: S
authors.lastname: Osowski
authors.forename: Tomasz
authors.initials: T
authors.lastname: Markiewicz
authors.forename: Janina
authors.initials: J
authors.lastname: Slodkowska
authors.forename: Robert
authors.initials: R
authors.lastname: Koktysz
authors.forename: Wojciech
authors.initials: W
authors.lastname: Kozlowski
authors.forename: Bartosz
authors.initials: B
authors.lastname: Swiderski
mesh_terms: D002292:Carcinoma, Renal Cell / Q000175:diagnosis / Q000473:pathology*; D003581:Cytodiagnosis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007680:Kidney Neoplasms / Q000175:diagnosis / Q000473:pathology*; D060787:Neoplasm Grading; D011379:Prognosis; D060388:Support Vector Machine