Amir, R. and Elham Dallalzadeh and Lalitha, R. (2013) Classification of medical imaging modalities based on visual and signal features. In: Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012).
Full text not available from this repository. (Request a copy)Abstract
In this paper, we present an approach to classify medical imaging modalities. Medical images are preprocessed in order to remove noises and enhance their content. The features based on texture, appearance and signal are extracted. The extracted features are concatenated to each other and considered for classification. KNN and SVM classifiers are applied to classify medical imaging modalities. The proposed approach is conducted on IMageCLEF2010 dataset. We achieve classification accuracy 95.39 % that presents the efficiency of our proposed approach.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Feature extraction, Image processing, Imaging modality, Medical imaging, Signal features, Texture features, Textures, Support vector machines, K-nearest neighbors, Appearance feature |
| Subjects: | D Physical Science > Computer Science |
| Divisions: | Department of > Computer Science |
| Depositing User: | Arshiya Kousar Library Assistant |
| Date Deposited: | 10 Dec 2019 06:24 |
| Last Modified: | 16 Jul 2022 07:09 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/9544 |
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