DocumentCode :
610898
Title :
Fuzzy Rough Set Approach for Selecting the Most Significant Texture Features in Mammogram Images
Author :
Alijla, B.O. ; Khader, Ahamad Tajudin ; Lim Chee Peng ; Al-betar, Mohammed Azmi ; Wong Li Pei
Author_Institution :
Sch. of Comput. Sci., Univ. Sains Malaysia (USM), Minden, Malaysia
fYear :
2013
fDate :
15-16 April 2013
Firstpage :
51
Lastpage :
56
Abstract :
Breast cancer is one of the most deadly related diseases in women across the world. The survival rate among the patients with the breast cancer will increase, if the disease is detected earlier. Mammogram analysis is one of the most promising methods that are being used in the early detection and abnormality classification of the breast cancer. Irrelevant and noisy features extracted from mammogram image often mislead the learning processes and also have negative impact on the quality of classification process. Therefore, this paper proposed the use of Fuzzy Rough Set Method to select the most significant texture features from mammogram images. Selected features are employed to build a more easy and understandable learning model in order to improve the classification quality of mammogram analysis systems. The results show that the proposed method selects the appropriate subset of features that are mostly representing the original data and increase the quality of classification.
Keywords :
cancer; feature extraction; fuzzy set theory; image classification; image texture; learning (artificial intelligence); mammography; medical image processing; rough set theory; breast cancer abnormality classification process quality; breast cancer detection; diseases; fuzzy rough set approach; learning processes; mammogram images; noisy feature extraction; original data representation; texture feature selection; Accuracy; Approximation methods; Breast cancer; Databases; Design automation; Equations; Feature extraction; Breast cancer; Feature selection; Fuzzy rough set; Mammogram analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology (PICICT), 2013 Palestinian International Conference on
Conference_Location :
Gaza
Print_ISBN :
978-1-4799-0137-1
Type :
conf
DOI :
10.1109/PICICT.2013.19
Filename :
6545937
Link To Document :
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