Publication:
A computational investigation of breast tumour on mammogram based on pattern of grey scale distribution
A computational investigation of breast tumour on mammogram based on pattern of grey scale distribution
| cris.author.scopus-author-id | 57212526813 | |
| cris.author.scopus-author-id | 57200576499 | |
| cris.author.scopus-author-id | 57219421621 | |
| dc.contributor.author | Lim M.K. | |
| dc.contributor.author | Khairunizam W. | |
| dc.contributor.author | Mustafa W.A. | |
| dc.date.accessioned | 2024-12-12T08:31:36Z | |
| dc.date.available | 2024-12-12T08:31:36Z | |
| dc.date.issued | 2019-01-01 | |
| dc.description.abstract | Breast cancer is the utmost female tumor and the primary cause of deaths among female. Computer-Aided Detection (CAD) systems are widely used as a tool to detect and classify the abnormalities found in the mammographic images. A detection of breast tumor in a mammogram has been a challenge due to the different intensity distribution which leads to the misdiagnosis of breast cancer. This research proposes a dectection system that is capable to detect the presence of mass tumor from a mammogram image. A total of 160 mammogram images are acquired from Mammographic Image Analysis Society (MIAS) databse, which are 80 normal and 80 abnormal images. The mammogram images are rescaled to 300 x 300 resolution. The noise in the mammogram is suppressed by using a Wiener filter. The images are enhanced by using Power Law (Gamma) Transformation, ɣ = 2 for a better image quality. The greyscale information that contain tumor mass is extracted and used to model the proposed detection system by using 80% or 128 and of the total 160 mammogram images. The rest 20% or 32 mammogram images are used to test the performance of the proposed detection system. The experimental results show that performance of the proposed detection system has 90.93% accuracy. | |
| dc.identifier.doi | 10.4028/www.scientific.net/JBBBE.43.67 | |
| dc.identifier.scopus | 2-s2.0-85077001439 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14170/10235 | |
| dc.relation.grantno | undefined | |
| dc.relation.ispartof | Journal of Biomimetics, Biomaterials and Biomedical Engineering | |
| dc.relation.ispartofseries | Journal of Biomimetics, Biomaterials and Biomedical Engineering | |
| dc.relation.issn | 22969837 | |
| dc.subject | Breast | Detection | Mammography | Tomour | |
| dc.title | A computational investigation of breast tumour on mammogram based on pattern of grey scale distribution | |
| dc.type | Journal | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 73 | |
| oaire.citation.startPage | 67 | |
| oaire.citation.volume | 43 | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| oairecerif.affiliation.orgunit | Universiti Malaysia Perlis | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| person.identifier.scopus-author-id | 57212526813 | |
| person.identifier.scopus-author-id | 57200576499 | |
| person.identifier.scopus-author-id | 57219421621 |