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(Aim) It is of great importance to find abnormal or pathological brains in the early stage, to save hospital and social resources. However, potential of wavelet-energy is not widely used in this field. (Method) The popular "wavelet-energy" is regarded as a prevalent feature descriptor, which achieves good performance in many applications. In this work, we propose a wavelet-energy based new...
In his paper a method of seizure detection has been proposed based on the Discrete Wavelet Transform (DWT) analysis of the dominant Intrinsic mode function(IMF) resulting from the Empirical Mode Decomposition(EMD) of the EEG signals. Considering the normalized energy, Fourier spectrum and cross-correlation coefficient analysis, only the 4th Level DWT coefficients of the dominant IMF is found reasonable...
In this paper, a method of seizure and non-seizure classification has been proposed based on the higher order statistics of the dominant Intrinsic mode function (IMF) resulting from the Empirical Mode Decomposition(EMD) of the EEG signals. Analyzing the temporal energy contents of different IMFs, it is found reasonable to determine the dominant IMF. In order to reduce the dimensionality, higher order...
Millions of people die from Diabetes Mellitus every year. Recently, researchers have discovered that Diabetes Mellitus can be detected in a non-invasive manner through the analysis of human facial blocks. Although algorithms have been developed to detect Diabetes Mellitus using facial block color features, use of its texture features to detect this disease has not been fully investigated. In this...
The cancer treatment is effective only if it is detected at an early stage. In this context, Mammography is the most efficient method for early detection. Due to the complexity of this last, the distinction of microcalcifications or opacities is very difficult. This paper deals with the problem of shape feature extraction in digital mammograms, particularly the boundary information. In fact, we evaluated...
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