Cardinal multiridgelet-based prostate cancer histological image classification for Gleason grading

Hong Jun Yoon, Ching Chung Li, Christhunesa Christudass, Robert Veltri, Jonathan I. Epstein, Zhen Zhang

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

Abstract

Computer-aided Gleason grading of prostate cancer tissue images has been in rapid development during the past decade. Automated classifiers using features derived from multi wavelet transform, fractal dimension and other measurements, and using text on forests have shown considerable successes. This paper presents our study on application of cardinal multiridgelet transform (CMRT) to prostate cancer images to extract texture features in the transform domain. CMRT can provide cardinality, approximate translation invariance and rotation invariance simultaneously. With 32 images of Gleason grade 3 and grade4 as a training set and using texture features extracted there from, a support vector machine with Gaussian kernel has been trained to classify grade 3 and grade 4. The leave-one-outcross-validation showed its accuracy of 93.75% and AUC of0.9651. 10 test images of grade 4 showed 100% accuracy.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
Pages315-320
Number of pages6
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011 - Atlanta, GA, United States
Duration: Nov 12 2011Nov 15 2011

Publication series

NameProceedings - 2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011

Other

Other2011 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2011
Country/TerritoryUnited States
CityAtlanta, GA
Period11/12/1111/15/11

Keywords

  • Complex Ridgelets
  • Gleason Grading
  • Multiridgelets
  • Multiwavelets
  • Prostate Cancer
  • Ridgelets
  • Tissue Texture Classification
  • Wavelets

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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