FussCyier: Mamogram images classification based on similarity measure fuzzy soft set
Automatic digital mammograms reading become highly enviable, as the number of mammograms to be examined by physician increases enormously.It is premised that the computer aided diagnosis system is mandatory to assist physicians/radiologists to achieve high efficiency and productivity.To handle unce...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2017
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| Online Access: | https://repo.uum.edu.my/id/eprint/22795/1/ICOCI%202017%2056-61.pdf |
| _version_ | 1803628433600675840 |
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| author | Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina |
| author_facet | Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina |
| author_sort | Lashari, Saima Anwar |
| collection | UUM |
| description | Automatic digital mammograms reading become highly enviable, as the number of mammograms to be examined by physician increases enormously.It is premised that the computer aided diagnosis system
is mandatory to assist physicians/radiologists to achieve high efficiency and productivity.To handle uncertainties of medical images, fuzzy soft set
theory has been merely scrutinized, even though the choice of convenient parameterization makes fuzzy soft set suitable and feasible for decision
making applications. Therefore, this study investigates the practicability of fuzzy soft set for classification of digital mammogram images to increase the classification accuracy while lower the classifier complexity.The proposed method FussCyier involves three phases namely: pre-processing, training and testing.Results of the research indicated that proposed method gives high classification performance with wavelet de-noise filter Sym8 with the accuracy 75.64%, recall 84.67% and CPU time 0.0026 seconds. |
| first_indexed | 2024-07-04T06:21:53Z |
| format | Conference or Workshop Item |
| id | uum-22795 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:21:53Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | uum-227952017-07-26T07:37:52Z https://repo.uum.edu.my/id/eprint/22795/ FussCyier: Mamogram images classification based on similarity measure fuzzy soft set Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina QA75 Electronic computers. Computer science Automatic digital mammograms reading become highly enviable, as the number of mammograms to be examined by physician increases enormously.It is premised that the computer aided diagnosis system is mandatory to assist physicians/radiologists to achieve high efficiency and productivity.To handle uncertainties of medical images, fuzzy soft set theory has been merely scrutinized, even though the choice of convenient parameterization makes fuzzy soft set suitable and feasible for decision making applications. Therefore, this study investigates the practicability of fuzzy soft set for classification of digital mammogram images to increase the classification accuracy while lower the classifier complexity.The proposed method FussCyier involves three phases namely: pre-processing, training and testing.Results of the research indicated that proposed method gives high classification performance with wavelet de-noise filter Sym8 with the accuracy 75.64%, recall 84.67% and CPU time 0.0026 seconds. 2017 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/22795/1/ICOCI%202017%2056-61.pdf Lashari, Saima Anwar and Ibrahim, Rosziati and Senan, Norhalina (2017) FussCyier: Mamogram images classification based on similarity measure fuzzy soft set. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap01e/PID186-56-61e.pdf |
| spellingShingle | QA75 Electronic computers. Computer science Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title | FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title_full | FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title_fullStr | FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title_full_unstemmed | FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title_short | FussCyier: Mamogram images classification based on similarity measure fuzzy soft set |
| title_sort | fusscyier mamogram images classification based on similarity measure fuzzy soft set |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/22795/1/ICOCI%202017%2056-61.pdf |
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