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The field of medical imaging gains its importance with increase in the need of automated and efficient diagnosis in a short period of time. Other than that, medical image retrieval system is to provide a tool for radiologists to retrieve the images similar to query image in content. Magnetic resonance imaging (MRI) is an imaging technique that has played an important role in neuroscience research...
Automatic analysis of cardiac arrhythmias is very important for diagnosis of cardiac abnormities. This paper presents a novel approach that classifies ECG signals with the combination of Wavelet transform and Decision tree classification. This approach has two aspects. In the first aspect, we utilize the wavelet transform to extract the ECG signals wavelet coefficients as the first features and utilize...
In this study, performance of wavelet transform based features for the speech / music discrimination task has been investigated. In order to extract wavelet domain features, discrete and complex wavelet transforms have been used. The performance of the proposed feature set has been compared with a feature set constructed from the most common time, frequency and cepstral domain features used in speech/music...
This paper proposes a novel idea based feature selection in the verification system of palmprint, which can realize the specific feature selection for different user using genetic algorithm (GA). In the stage of enrollment, discrete wavelet transforms (DWT) and statistical methods are first used for feature extraction. Then GA is employed for feature selection, which means that each user has a specific...
In this paper we report our experience using different types of wavelets and different SVM kernel functions for classification of Magnetic Resonance Images to identify those showing symptoms of Alzheimer's Disease. We have developed a novel computational framework for extracting discriminative Gabor wavelet features from the images for classification using Support Vector Machines with various kernel...
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