Classification of medical imaging modalities based on visual and signal features

Rajaei, A. and Dallalzadeh, E. and Rangarajan, L. (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).

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Official URL: http://doi.org/10.1007/978-81-322-1000-9_44

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
Date Deposited: 10 Dec 2019 06:24
Last Modified: 10 Dec 2019 06:24
URI: http://eprints.uni-mysore.ac.in/id/eprint/9544

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