Diagnosis system for the detection of abnormal tissues from brain MRI
The brain tumor is widely disseminating disease all over the world and causing the increasing death rates. If the tumor is diagnosed at early stages, the increasing death rate can be decreased to some extent. Manual segmentation of brain MR images by experts is very expensive, non-repeatable and tim...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Zhengzhou University
2013
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| Online Access: | http://ir.unimas.my/id/eprint/15951/ http://ir.unimas.my/id/eprint/15951/1/Diagnosis.pdf |
| _version_ | 1848837959089913856 |
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| author | Arshad, Javed Abdulhameed, Rakan Alenezi Wang, Yin Chai Narayanan, Kulathuramaiyer |
| author_facet | Arshad, Javed Abdulhameed, Rakan Alenezi Wang, Yin Chai Narayanan, Kulathuramaiyer |
| author_sort | Arshad, Javed |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The brain tumor is widely disseminating disease all over the world and causing the increasing death rates. If the tumor is diagnosed at early stages, the increasing death rate can be decreased to some extent. Manual segmentation of brain MR images by experts is very expensive, non-repeatable and time consuming task. The computer-aided diagnosis system assists experts to take the opinion to diagnose the disease severity. The diagnosis process can be affected if the images are low contrast or poor quality and wrong diagnoses chances become high. The objective of this paper is to establish an automatic, accurate, fast and reliable diagnosis system which could be able to diagnose the brain tumor and also extract the region of the brain tumor from brain MR images. The median filter is used for enhancing the poor quality image, fuzzy c-means clustering technique for segmentation of images and mathematical morphological operations are performed to extract the abnormal portion from images. The proposed technique is applied on different brain MR images for both visual evaluations and quantitative. Experimental results of the proposed method showed, the proposed approach provides a fast, effective and promising method for the brain tumor extraction from MR images with high accuracy. |
| first_indexed | 2025-11-15T06:47:56Z |
| format | Article |
| id | unimas-15951 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:47:56Z |
| publishDate | 2013 |
| publisher | Zhengzhou University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-159512023-05-29T01:21:10Z http://ir.unimas.my/id/eprint/15951/ Diagnosis system for the detection of abnormal tissues from brain MRI Arshad, Javed Abdulhameed, Rakan Alenezi Wang, Yin Chai Narayanan, Kulathuramaiyer QA76 Computer software RD Surgery The brain tumor is widely disseminating disease all over the world and causing the increasing death rates. If the tumor is diagnosed at early stages, the increasing death rate can be decreased to some extent. Manual segmentation of brain MR images by experts is very expensive, non-repeatable and time consuming task. The computer-aided diagnosis system assists experts to take the opinion to diagnose the disease severity. The diagnosis process can be affected if the images are low contrast or poor quality and wrong diagnoses chances become high. The objective of this paper is to establish an automatic, accurate, fast and reliable diagnosis system which could be able to diagnose the brain tumor and also extract the region of the brain tumor from brain MR images. The median filter is used for enhancing the poor quality image, fuzzy c-means clustering technique for segmentation of images and mathematical morphological operations are performed to extract the abnormal portion from images. The proposed technique is applied on different brain MR images for both visual evaluations and quantitative. Experimental results of the proposed method showed, the proposed approach provides a fast, effective and promising method for the brain tumor extraction from MR images with high accuracy. Zhengzhou University 2013 Article PeerReviewed text en http://ir.unimas.my/id/eprint/15951/1/Diagnosis.pdf Arshad, Javed and Abdulhameed, Rakan Alenezi and Wang, Yin Chai and Narayanan, Kulathuramaiyer (2013) Diagnosis system for the detection of abnormal tissues from brain MRI. Life Science Journal, 10 (2). pp. 1949-1955. ISSN 1097-8135 http://www.lifesciencesite.com/ |
| spellingShingle | QA76 Computer software RD Surgery Arshad, Javed Abdulhameed, Rakan Alenezi Wang, Yin Chai Narayanan, Kulathuramaiyer Diagnosis system for the detection of abnormal tissues from brain MRI |
| title | Diagnosis system for the detection of abnormal tissues from brain MRI |
| title_full | Diagnosis system for the detection of abnormal tissues from brain MRI |
| title_fullStr | Diagnosis system for the detection of abnormal tissues from brain MRI |
| title_full_unstemmed | Diagnosis system for the detection of abnormal tissues from brain MRI |
| title_short | Diagnosis system for the detection of abnormal tissues from brain MRI |
| title_sort | diagnosis system for the detection of abnormal tissues from brain mri |
| topic | QA76 Computer software RD Surgery |
| url | http://ir.unimas.my/id/eprint/15951/ http://ir.unimas.my/id/eprint/15951/ http://ir.unimas.my/id/eprint/15951/1/Diagnosis.pdf |