Mass detection in mammograms using ga based PCA and Haralick features selection
Many existing researches utilized different types of feature extraction techniques to detect masses in ROI images. Based on our observations, inclusion of additional features beyond a certain point worsens the performance rather than enhancing it. This paper describes a hybrid method of mammogram re...
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| creator | Amroabadi, SayedMasoud Hashemi Ahmadzadeh, Mohammad Reza Hekmatnia, Ali |
| description | Many existing researches utilized different types of feature extraction techniques to detect masses in ROI images. Based on our observations, inclusion of additional features beyond a certain point worsens the performance rather than enhancing it. This paper describes a hybrid method of mammogram recognition which is based on principle component analysis, Haralick features and Genetic algorithm to select the best features. |
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Based on our observations, inclusion of additional features beyond a certain point worsens the performance rather than enhancing it. This paper describes a hybrid method of mammogram recognition which is based on principle component analysis, Haralick features and Genetic algorithm to select the best features.</abstract><pub>IEEE</pub></addata></record> |
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| ispartof | 2011 19th Iranian Conference on Electrical Engineering, 2011, p.1-4 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis Classification algorithms co-occurrence matrices component analysis Digital mammography Feature extraction Genetic algorithm Genetic algorithms Lesions Principal component analysis Support vector machine classification |
| title | Mass detection in mammograms using ga based PCA and Haralick features selection |
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