Medical image classification and symptoms detection using neuro fuzzy
The conventional method in medicine for brain MR images classification and tumor detection is by human inspection. Operator-assisted classification methods are impractical for large amounts of data and are also non-reproducible. MR images also always contain a noise caused by operator performance wh...
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| Format: | Thesis |
| Language: | English |
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2008
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| Online Access: | http://eprints.utm.my/9503/1/MohdAriffananMFKE2008.pdf |
| _version_ | 1796854525861036032 |
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| author | Mohd. Basri, Mohd. Ariffanan |
| author_facet | Mohd. Basri, Mohd. Ariffanan |
| author_sort | Mohd. Basri, Mohd. Ariffanan |
| collection | ePrints |
| description | The conventional method in medicine for brain MR images classification and tumor detection is by human inspection. Operator-assisted classification methods are impractical for large amounts of data and are also non-reproducible. MR images also always contain a noise caused by operator performance which can lead to serious inaccuracies classification. The use of artificial intelligent techniques, for instance, neural networks, fuzzy logic, neuro fuzzy have shown great potential in this field. Hence, in this project the neuro fuzzy system or ANFIS was applied for classification and detection purposes. Decision making was performed in two stages: feature extraction using the principal component analysis (PCA) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. The performance of the ANFIS classifier was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS classifier has potential in detecting the tumors. |
| first_indexed | 2024-03-05T18:15:22Z |
| format | Thesis |
| id | utm.eprints-9503 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:15:22Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | utm.eprints-95032018-07-19T01:51:05Z http://eprints.utm.my/9503/ Medical image classification and symptoms detection using neuro fuzzy Mohd. Basri, Mohd. Ariffanan RZ Other systems of medicine TK Electrical engineering. Electronics Nuclear engineering QA76 Computer software The conventional method in medicine for brain MR images classification and tumor detection is by human inspection. Operator-assisted classification methods are impractical for large amounts of data and are also non-reproducible. MR images also always contain a noise caused by operator performance which can lead to serious inaccuracies classification. The use of artificial intelligent techniques, for instance, neural networks, fuzzy logic, neuro fuzzy have shown great potential in this field. Hence, in this project the neuro fuzzy system or ANFIS was applied for classification and detection purposes. Decision making was performed in two stages: feature extraction using the principal component analysis (PCA) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. The performance of the ANFIS classifier was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS classifier has potential in detecting the tumors. 2008-11 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/9503/1/MohdAriffananMFKE2008.pdf Mohd. Basri, Mohd. Ariffanan (2008) Medical image classification and symptoms detection using neuro fuzzy. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:855?site_name=Restricted Repository |
| spellingShingle | RZ Other systems of medicine TK Electrical engineering. Electronics Nuclear engineering QA76 Computer software Mohd. Basri, Mohd. Ariffanan Medical image classification and symptoms detection using neuro fuzzy |
| title | Medical image classification and symptoms detection using neuro fuzzy |
| title_full | Medical image classification and symptoms detection using neuro fuzzy |
| title_fullStr | Medical image classification and symptoms detection using neuro fuzzy |
| title_full_unstemmed | Medical image classification and symptoms detection using neuro fuzzy |
| title_short | Medical image classification and symptoms detection using neuro fuzzy |
| title_sort | medical image classification and symptoms detection using neuro fuzzy |
| topic | RZ Other systems of medicine TK Electrical engineering. Electronics Nuclear engineering QA76 Computer software |
| url | http://eprints.utm.my/9503/1/MohdAriffananMFKE2008.pdf |
| work_keys_str_mv | AT mohdbasrimohdariffanan medicalimageclassificationandsymptomsdetectionusingneurofuzzy |