A Method for Identification and Visualization of Histological Image Structures Relevant to the Cancer Patient Conditions

  • Vassili Kovalev
  • Alexander Dmitruk
  • Ihar Safonau
  • Mikhail Frydman
  • Sviatlana Shelkovich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6854)


A method is suggested for identification and visualization of histology image structures relevant to the key characteristics of the state of cancer patients. The method is based on a multi-step procedure which includes calculating image descriptors, extracting their principal components, correlating them to known object properties and mapping disclosed regularities all the way back up to the corresponding image structures they found to be linked with. Image descriptors employed are extended 4D color co-occurrence matrices counting the occurrence of all possible pixel triplets located at the vertices of equilateral triangles of different size. The method is demonstrated on a sample of 952 histology images taken from 68 women with clinically confirmed diagnosis of ovarian cancer. As a result, a number of associations between the patients’ conditions and morphological image structures were found including both easily explainable and the ones whose biological substrate remains obscured.


Ovarian Cancer Ovarian Cancer Patient Image Structure Image Mining Histological Image 
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 2011

Authors and Affiliations

  • Vassili Kovalev
    • 1
  • Alexander Dmitruk
    • 1
  • Ihar Safonau
    • 1
  • Mikhail Frydman
    • 2
  • Sviatlana Shelkovich
    • 3
  1. 1.Biomedical Image Analysis DepartmentUnited Institute of Informatics ProblemsMinsk
  2. 2.Department of Morbid AnatomyMinsk City Hospital for OncologyMinsk
  3. 3.Oncology DepartmentBelarusian Medical Academy of Post-Graduate EducationMinsk

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