Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images

Parmeshwar Khurd, Leo Grady, Ali Kamen, Summer Gibbs-Strauss, Elizabeth M. Genega, John V. Frangioni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Scopus citations

Abstract

Features extracted from cell networks have become popular tools in histological image analysis. However, existing features do not take sufficient advantage of the cycle structure present within the cell networks. We introduce a new class of network cycle features that take advantage of such structures. We demonstrate the utility of these features for automated prostate cancer scoring using histological images. Prostate cancer is commonly scored by pathologists using the Gleason grading system and our automated system based upon network cycle features serves an important need in making this process less labor-intensive and more reproducible. Our system first extracts the cells from the histological images, computes networks from the cell locations and then computes features based upon statistics for the different cycles present in these networks. Using an SVM (Support Vector Machine) classifier on these features, we demonstrate the efficacy of our system in distinguishing between grade 3 and grade 4 prostate tumors. We also show the superiority of our approach over previously developed systems for this problem based upon texture features, fractal features and alternative network features.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages1632-1636
Number of pages5
DOIs
StatePublished - Nov 2 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

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Keywords

  • Gleason grading
  • classification
  • network features
  • prostate cancer

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Khurd, P., Grady, L., Kamen, A., Gibbs-Strauss, S., Genega, E. M., & Frangioni, J. V. (2011). Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 1632-1636). [5872716] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872716