Fuzzy rough set approach for selecting the most significant texture features in mammogram images

Basem O. Alijla; Ahamad Tajudin Khader; Lim Chee Peng; Mohammed Azmi Al-Betar; Wong Li Pei

doi:10.1109/PICICT.2013.1

Fuzzy rough set approach for selecting the most significant texture features in mammogram images

Basem O. Alijla
, Ahamad Tajudin Khader
, Lim Chee Peng
, Mohammed Azmi Al-Betar
, Wong Li Pei

Universiti Sains Malaysia
Deakin University
Jadara University

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

3 Scopus citations

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.

Original language	English
Title of host publication	Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013
Pages	51-56
Number of pages	6
DOIs	https://doi.org/10.1109/PICICT.2013.1
State	Published - 2013
Externally published	Yes
Event	2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013 - Gaza, Gaza Strip, Palestine, State of Duration: 15 Apr 2013 → 16 Apr 2013

Publication series

Name	Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013

Conference

Conference	2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013
Country/Territory	Palestine, State of
City	Gaza, Gaza Strip
Period	15/04/13 → 16/04/13

UN SDGs

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

SDG 3 Good Health and Well-being

Access to Document

10.1109/PICICT.2013.1

Cite this

Alijla, B. O., Khader, A. T., Peng, L. C., Al-Betar, M. A., & Pei, W. L. (2013). Fuzzy rough set approach for selecting the most significant texture features in mammogram images. In Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013 (pp. 51-56). Article 6545937 (Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013). https://doi.org/10.1109/PICICT.2013.1

Alijla, Basem O. ; Khader, Ahamad Tajudin ; Peng, Lim Chee et al. / Fuzzy rough set approach for selecting the most significant texture features in mammogram images. Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013. 2013. pp. 51-56 (Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013).

@inproceedings{40842c5f49a54a26be3652fc9f976974,

title = "Fuzzy rough set approach for selecting the most significant texture features in mammogram images",

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.",

author = "Alijla, \{Basem O.\} and Khader, \{Ahamad Tajudin\} and Peng, \{Lim Chee\} and Al-Betar, \{Mohammed Azmi\} and Pei, \{Wong Li\}",

year = "2013",

doi = "10.1109/PICICT.2013.1",

language = "English",

isbn = "9780769549842",

series = "Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013",

pages = "51--56",

booktitle = "Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013",

note = "2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013 ; Conference date: 15-04-2013 Through 16-04-2013",

}

Alijla, BO, Khader, AT, Peng, LC, Al-Betar, MA & Pei, WL 2013, Fuzzy rough set approach for selecting the most significant texture features in mammogram images. in Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013., 6545937, Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013, pp. 51-56, 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013, Gaza, Gaza Strip, Palestine, State of, 15/04/13. https://doi.org/10.1109/PICICT.2013.1

Fuzzy rough set approach for selecting the most significant texture features in mammogram images. / Alijla, Basem O.; Khader, Ahamad Tajudin; Peng, Lim Chee et al.
Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013. 2013. p. 51-56 6545937 (Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013).

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

TY - GEN

T1 - Fuzzy rough set approach for selecting the most significant texture features in mammogram images

AU - Alijla, Basem O.

AU - Khader, Ahamad Tajudin

AU - Peng, Lim Chee

AU - Al-Betar, Mohammed Azmi

AU - Pei, Wong Li

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/84881176769

U2 - 10.1109/PICICT.2013.1

DO - 10.1109/PICICT.2013.1

M3 - Conference contribution

AN - SCOPUS:84881176769

SN - 9780769549842

T3 - Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013

SP - 51

EP - 56

BT - Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013

T2 - 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013

Y2 - 15 April 2013 through 16 April 2013

ER -

Alijla BO, Khader AT, Peng LC, Al-Betar MA, Pei WL. Fuzzy rough set approach for selecting the most significant texture features in mammogram images. In Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013. 2013. p. 51-56. 6545937. (Proceedings of the 2013 Palestinian International Conference on Information and Communication Technology, PICICT 2013). doi: 10.1109/PICICT.2013.1

Fuzzy rough set approach for selecting the most significant texture features in mammogram images

Abstract

Publication series

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this