Gleason grade-based automatic classification of prostate cancer pathological images

Ali Almuntashri, Sos Agaian, Ian Thompson, Danny Rabah, Osman Zin Al-Abdin, Marlo Nicolas

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

12 Citations (Scopus)

Abstract

In this Paper, we introduce a new method for automatic recognition and classification of prostate cancer biopsy images based on Gleason grading system. The introduced algorithm combines features from wavelet transform and fractal analysis domains. Biopsy images are pre-processed prior to features extraction using effective image processing algorithms to analyze textural complexity in terms of RGB color channels, edge and segmentation information. Experimental results achieved an average classification accuracy of 95 % in a set of 45 images with diversities in resolution, magnification levels, and stain colors.

Original languageEnglish (US)
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages2696-2701
Number of pages6
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Anchorage, AK, United States
Duration: Oct 9 2011Oct 12 2011

Other

Other2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011
CountryUnited States
CityAnchorage, AK
Period10/9/1110/12/11

Fingerprint

Biopsy
Color
Fractals
Wavelet transforms
Feature extraction
Image processing

Keywords

  • fractal dimension
  • Gleason grading
  • Prostate cancer
  • statistical classification
  • wavelet features

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

Cite this

Almuntashri, A., Agaian, S., Thompson, I., Rabah, D., Zin Al-Abdin, O., & Nicolas, M. (2011). Gleason grade-based automatic classification of prostate cancer pathological images. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (pp. 2696-2701). [6084080] https://doi.org/10.1109/ICSMC.2011.6084080

Gleason grade-based automatic classification of prostate cancer pathological images. / Almuntashri, Ali; Agaian, Sos; Thompson, Ian; Rabah, Danny; Zin Al-Abdin, Osman; Nicolas, Marlo.

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2011. p. 2696-2701 6084080.

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

Almuntashri, A, Agaian, S, Thompson, I, Rabah, D, Zin Al-Abdin, O & Nicolas, M 2011, Gleason grade-based automatic classification of prostate cancer pathological images. in Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics., 6084080, pp. 2696-2701, 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011, Anchorage, AK, United States, 10/9/11. https://doi.org/10.1109/ICSMC.2011.6084080
Almuntashri A, Agaian S, Thompson I, Rabah D, Zin Al-Abdin O, Nicolas M. Gleason grade-based automatic classification of prostate cancer pathological images. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2011. p. 2696-2701. 6084080 https://doi.org/10.1109/ICSMC.2011.6084080
Almuntashri, Ali ; Agaian, Sos ; Thompson, Ian ; Rabah, Danny ; Zin Al-Abdin, Osman ; Nicolas, Marlo. / Gleason grade-based automatic classification of prostate cancer pathological images. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics. 2011. pp. 2696-2701
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