Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images
Brain cancer has remained one of the key causes of deaths in people of all ages. One way to survival amongst patients is to correctly diagnose cancer in its early stages. Recently machine learning has become a very important tool in medical image classification. Our approach is to examine and compa...
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| Format: | Article |
| Language: | English |
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Sir Syed University of Engineering and Technology, Karachi.
2018-12-01
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| Series: | Sir Syed University Research Journal of Engineering and Technology |
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| Online Access: | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/36 |
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| _version_ | 1849434307383263232 |
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| author | Lubna Farhi Razia Zia Zain Anwar Ali |
| author_facet | Lubna Farhi Razia Zia Zain Anwar Ali |
| author_sort | Lubna Farhi |
| collection | DOAJ |
| description |
Brain cancer has remained one of the key causes of deaths in people of all ages. One way to survival amongst patients is to correctly diagnose cancer in its early stages. Recently machine learning has become a very important tool in medical image classification. Our approach is to examine and compare various machine learning classification algorithms that help in brain tumor classification of Magnetic Resonance (MR) images. We have compared Artificial Neural Network (ANN), K-nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine
(SVM) and Naïve Bayes (NB) classifiers to determine the accuracy of each classifier and find the best amongst them for classification of cancerous and noncancerous brain MR images. We have used 86 MR images and extracted a large number of features for each image. Since the equal number of images, have been used thus there is no suspicion of results being biased. For our data set the most accurate results were provided by ANN. It was found that ANN provides better results for medium to large database of Brain MR Images.
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| format | Article |
| id | doaj-art-c15ac81482da46a688d8deaec1bb152b |
| institution | Kabale University |
| issn | 1997-0641 2415-2048 |
| language | English |
| publishDate | 2018-12-01 |
| publisher | Sir Syed University of Engineering and Technology, Karachi. |
| record_format | Article |
| series | Sir Syed University Research Journal of Engineering and Technology |
| spelling | doaj-art-c15ac81482da46a688d8deaec1bb152b2025-08-20T03:26:43ZengSir Syed University of Engineering and Technology, Karachi.Sir Syed University Research Journal of Engineering and Technology1997-06412415-20482018-12-0181Performance Analysis of Machine Learning Classifiers for Brain Tumor MR ImagesLubna FarhiRazia ZiaZain Anwar Ali Brain cancer has remained one of the key causes of deaths in people of all ages. One way to survival amongst patients is to correctly diagnose cancer in its early stages. Recently machine learning has become a very important tool in medical image classification. Our approach is to examine and compare various machine learning classification algorithms that help in brain tumor classification of Magnetic Resonance (MR) images. We have compared Artificial Neural Network (ANN), K-nearest Neighbor (KNN), Decision Tree (DT), Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers to determine the accuracy of each classifier and find the best amongst them for classification of cancerous and noncancerous brain MR images. We have used 86 MR images and extracted a large number of features for each image. Since the equal number of images, have been used thus there is no suspicion of results being biased. For our data set the most accurate results were provided by ANN. It was found that ANN provides better results for medium to large database of Brain MR Images. http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/36ANN, SVM, NB, DT, KNN and GLCM. |
| spellingShingle | Lubna Farhi Razia Zia Zain Anwar Ali Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images Sir Syed University Research Journal of Engineering and Technology ANN, SVM, NB, DT, KNN and GLCM. |
| title | Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images |
| title_full | Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images |
| title_fullStr | Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images |
| title_full_unstemmed | Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images |
| title_short | Performance Analysis of Machine Learning Classifiers for Brain Tumor MR Images |
| title_sort | performance analysis of machine learning classifiers for brain tumor mr images |
| topic | ANN, SVM, NB, DT, KNN and GLCM. |
| url | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/36 |
| work_keys_str_mv | AT lubnafarhi performanceanalysisofmachinelearningclassifiersforbraintumormrimages AT raziazia performanceanalysisofmachinelearningclassifiersforbraintumormrimages AT zainanwarali performanceanalysisofmachinelearningclassifiersforbraintumormrimages |