Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques
Segmentation is usually conceived as a compulsory phase for the analysis and classification to the field of medical imaging. The aim of the paper is to find a means for the segmentation of brain from MR images by technique of combining Contourlet Transform and K-Means Clustering in an automatic way....
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publishing Network (ARPN)
2013
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/16526/ http://ir.unimas.my/id/eprint/16526/1/ARSHAD%20JAVED.pdf |
| _version_ | 1848838080953319424 |
|---|---|
| author | Arshad, Javed Wang, Yin Chai Narayanan, Kulathuramaiyer Muhammad Salim, Javed Abdulhameed, Rakan Alenezi |
| author_facet | Arshad, Javed Wang, Yin Chai Narayanan, Kulathuramaiyer Muhammad Salim, Javed Abdulhameed, Rakan Alenezi |
| author_sort | Arshad, Javed |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Segmentation is usually conceived as a compulsory phase for the analysis and classification to the field of medical imaging. The aim of the paper is to find a means for the segmentation of brain from MR images by technique of combining Contourlet Transform and K-Means Clustering in an automatic way. De-noising is always an exigent problem in magnetic resonance imaging and significant for clinical diagnosis and computerized analysis such as tissue classification and segmentation. In this paper Contourlet transform has been used for noise removal and enhancement for the image superiority. The proposed technique is exclusively based upon the information enclosed within the image. There is no need for human interventions and extra information about the system. This technique has been tested on different types of MR images, and conclusion had been concluded. |
| first_indexed | 2025-11-15T06:49:52Z |
| format | Article |
| id | unimas-16526 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:49:52Z |
| publishDate | 2013 |
| publisher | Asian Research Publishing Network (ARPN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-165262023-05-26T07:07:58Z http://ir.unimas.my/id/eprint/16526/ Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques Arshad, Javed Wang, Yin Chai Narayanan, Kulathuramaiyer Muhammad Salim, Javed Abdulhameed, Rakan Alenezi R Medicine (General) T Technology (General) Segmentation is usually conceived as a compulsory phase for the analysis and classification to the field of medical imaging. The aim of the paper is to find a means for the segmentation of brain from MR images by technique of combining Contourlet Transform and K-Means Clustering in an automatic way. De-noising is always an exigent problem in magnetic resonance imaging and significant for clinical diagnosis and computerized analysis such as tissue classification and segmentation. In this paper Contourlet transform has been used for noise removal and enhancement for the image superiority. The proposed technique is exclusively based upon the information enclosed within the image. There is no need for human interventions and extra information about the system. This technique has been tested on different types of MR images, and conclusion had been concluded. Asian Research Publishing Network (ARPN) 2013 Article PeerReviewed text en http://ir.unimas.my/id/eprint/16526/1/ARSHAD%20JAVED.pdf Arshad, Javed and Wang, Yin Chai and Narayanan, Kulathuramaiyer and Muhammad Salim, Javed and Abdulhameed, Rakan Alenezi (2013) Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques. Journal of Theoretical and Applied Information Technology, 54 (1). pp. 82-91. ISSN 1992-8645 http:///www.jatit.org/ |
| spellingShingle | R Medicine (General) T Technology (General) Arshad, Javed Wang, Yin Chai Narayanan, Kulathuramaiyer Muhammad Salim, Javed Abdulhameed, Rakan Alenezi Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title | Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title_full | Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title_fullStr | Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title_full_unstemmed | Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title_short | Automated segmentation of brain MR images by combining Contourlet Transform and K-means Clustering techniques |
| title_sort | automated segmentation of brain mr images by combining contourlet transform and k-means clustering techniques |
| topic | R Medicine (General) T Technology (General) |
| url | http://ir.unimas.my/id/eprint/16526/ http://ir.unimas.my/id/eprint/16526/ http://ir.unimas.my/id/eprint/16526/1/ARSHAD%20JAVED.pdf |