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In this paper, a new approach for non-invasive diagnosis of breast diseases is tested on the region of the breast without undue influence from the background and medically unnecessary parts of the images. We applied Wavelet packet analysis on the two-dimensional histogram matrices of a large number of breast images to generate the filter banks, namely sub-images. Each of 1250 resulting sub-images...
In this paper, we are going to evaluate the role of nonlinear feature, fractal dimension, in discriminating patients with speech disorders from normal subjects. Laryngeal pathologies usually cause an asymmetry in oscillation of vocal folds. This leads to sub-harmonics and chaos in generated voices. In such condition, using nonlinear dynamic features, like fractal dimension, seems to be efficient approach...
The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's disease (AD) which appeared in patient's brain. The features of interest are categorized in features of the spatial domain (FSD's) and Features of the frequency domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer...
In this study, we have proposed a novel approach to investigate the features of four subbands of 2-D wavelet transform in magnetic resonance images (MRIs) for normal and abnormal brains which defected by multiple sclerosis (MS). Concurrently, another method extracts different kinds of features in spatial domain. Totally, 116 features have been extracted. Before applying the algorithm, we have to use...
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