Breast cancer detection based on statistical textural features classification

Al Mutaz M. Abdalla; Safaai Deris; Nazar Zaki; Doaa M. Ghoneim

doi:10.1109/IIT.2007.4430510

Breast cancer detection based on statistical textural features classification

Al Mutaz M. Abdalla
, Safaai Deris
, Nazar Zaki
, Doaa M. Ghoneim

Department of Computer Science and Software Engineering

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

18 Citations (Scopus)

Abstract

Localized textural analysis of breast tissue on mammograms has recently gained considerable attention by researchers studying breast cancer detection. Despite the research progress to solve the problem, detecting breast cancer based on textural features has not been investigated in depth. In this paper we study the breast cancer detection based on statistical texture features using Support Vector Machine (SVM). A set of textural features was applied to a set of 120 digital mammographic images, from the Digital Database for Screening Mammography. These features are then used in conjunction with SVMs to detect the breast cancer. Other linear and non-linear classifiers were also employed to be compared to the SVM performance. SVM was able to achieve better classification accuracy of 82.5%.

Original language	English
Title of host publication	Innovations'07
Subtitle of host publication	4th International Conference on Innovations in Information Technology, IIT
Publisher	IEEE Computer Society
Pages	728-730
Number of pages	3
ISBN (Print)	9781424418411
DOIs	https://doi.org/10.1109/IIT.2007.4430510
Publication status	Published - 2007
Event	Innovations'07: 4th International Conference on Innovations in Information Technology, IIT - Dubai, United Arab Emirates Duration: Nov 18 2007 → Nov 20 2007

Publication series

Name	Innovations'07: 4th International Conference on Innovations in Information Technology, IIT

Other

Other	Innovations'07: 4th International Conference on Innovations in Information Technology, IIT
Country/Territory	United Arab Emirates
City	Dubai
Period	11/18/07 → 11/20/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems

Access to Document

10.1109/IIT.2007.4430510

Cite this

Abdalla, A. M. M., Deris, S., Zaki, N., & Ghoneim, D. M. (2007). Breast cancer detection based on statistical textural features classification. In Innovations'07: 4th International Conference on Innovations in Information Technology, IIT (pp. 728-730). Article 4430510 (Innovations'07: 4th International Conference on Innovations in Information Technology, IIT). IEEE Computer Society. https://doi.org/10.1109/IIT.2007.4430510

Breast cancer detection based on statistical textural features classification. / Abdalla, Al Mutaz M.; Deris, Safaai; Zaki, Nazar et al.
Innovations'07: 4th International Conference on Innovations in Information Technology, IIT. IEEE Computer Society, 2007. p. 728-730 4430510 (Innovations'07: 4th International Conference on Innovations in Information Technology, IIT).

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

Abdalla, AMM, Deris, S, Zaki, N & Ghoneim, DM 2007, Breast cancer detection based on statistical textural features classification. in Innovations'07: 4th International Conference on Innovations in Information Technology, IIT., 4430510, Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, IEEE Computer Society, pp. 728-730, Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, United Arab Emirates, 11/18/07. https://doi.org/10.1109/IIT.2007.4430510

Abdalla AMM, Deris S, Zaki N, Ghoneim DM. Breast cancer detection based on statistical textural features classification. In Innovations'07: 4th International Conference on Innovations in Information Technology, IIT. IEEE Computer Society. 2007. p. 728-730. 4430510. (Innovations'07: 4th International Conference on Innovations in Information Technology, IIT). doi: 10.1109/IIT.2007.4430510

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abstract = "Localized textural analysis of breast tissue on mammograms has recently gained considerable attention by researchers studying breast cancer detection. Despite the research progress to solve the problem, detecting breast cancer based on textural features has not been investigated in depth. In this paper we study the breast cancer detection based on statistical texture features using Support Vector Machine (SVM). A set of textural features was applied to a set of 120 digital mammographic images, from the Digital Database for Screening Mammography. These features are then used in conjunction with SVMs to detect the breast cancer. Other linear and non-linear classifiers were also employed to be compared to the SVM performance. SVM was able to achieve better classification accuracy of 82.5\%.",

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AB - Localized textural analysis of breast tissue on mammograms has recently gained considerable attention by researchers studying breast cancer detection. Despite the research progress to solve the problem, detecting breast cancer based on textural features has not been investigated in depth. In this paper we study the breast cancer detection based on statistical texture features using Support Vector Machine (SVM). A set of textural features was applied to a set of 120 digital mammographic images, from the Digital Database for Screening Mammography. These features are then used in conjunction with SVMs to detect the breast cancer. Other linear and non-linear classifiers were also employed to be compared to the SVM performance. SVM was able to achieve better classification accuracy of 82.5%.

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Breast cancer detection based on statistical textural features classification

Abstract

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UN SDGs

ASJC Scopus subject areas

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