Gleason grade-based automatic classification of prostate cancer pathological images

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

doi:10.1109/ICSMC.2011.6084080

Gleason grade-based automatic classification of prostate cancer pathological images

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

Department of Pathology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Scopus citations

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 language	English (US)
Title of host publication	2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest
Pages	2696-2701
Number of pages	6
DOIs	https://doi.org/10.1109/ICSMC.2011.6084080
State	Published - 2011
Event	2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Anchorage, AK, United States Duration: Oct 9 2011 → Oct 12 2011

Publication series

Name	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)	1062-922X

Other

Other	2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011
Country/Territory	United States
City	Anchorage, AK
Period	10/9/11 → 10/12/11

Keywords

Gleason grading
Prostate cancer
fractal dimension
statistical classification
wavelet features

ASJC Scopus subject areas

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

Access to Document

10.1109/ICSMC.2011.6084080

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 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest (pp. 2696-2701). [6084080] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2011.6084080

Gleason grade-based automatic classification of prostate cancer pathological images. / Almuntashri, Ali; Agaian, Sos; Thompson, Ian et al.

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

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest., 6084080, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 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 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 - Conference Digest. 2011. p. 2696-2701. 6084080. (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). doi: 10.1109/ICSMC.2011.6084080

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Gleason grade-based automatic classification of prostate cancer pathological images

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Keywords

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