M. Abdalla, Al Mumtaz and Deris, Safaai and Nazar, Zaki and Ghoneim, Doaa M. (2008) Breast cancer detection based on statistical textural features classification. In: Innovations'07: 4th International Conference on Innovations in Information Technology, IIT.
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Official URL: http://dx.doi.org/10.1109/IIT.2007.4430510
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%.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||T Technology > T Technology (General)|
|Deposited By:||Nur Amal Zakiah Shamsudin|
|Deposited On:||02 Jan 2009 07:30|
|Last Modified:||01 Jun 2010 15:51|
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