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For any respiratory sound analysis or assessment, respiratory flow must also be measured simultaneously with the sounds. However, due to difficulties and/or inaccuracy of the most flow measurement techniques, several researchers have attempted to estimate flow from respiratory sounds. However, all of the proposed methods heavily depend on the availability of different rates of flow for calibration...
Electroencephalographic (EEG) signals are normally acquired in the presence of background noise which causes inaccurate or false entropy measurement throughout the signal. In this paper, spectral subtraction is used to pre-process EEG signals to improve the accuracy of computing the subband wavelet entropy (SWE). The silent period in the EEG signal is identified via cepstral distance which allows...
The degree of hand pressure applied on a breast determines the possibilities of lump detection during breast self-examination. In this paper, a method for estimating hand pressure is presented by means of analysing image entropy for an image sequence obtained through a Web camera. This is achieved by, firstly, calculating the difference between the current and initial images followed by the entropy...
A very important artifact corrupting magnetic resonance images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present...
Symbolic dynamics is a useful tool in several fields of complexity analysis in nonlinear science. In order to investigate complexities of the human brain electrical activities under different brain functional states, a novel method in terms of symbolic entropy is defined and proposed in this paper. The novel algorithm based on symbolic dynamics is developed for quantitatively measuring the complexity...
This study described a novel method for preparing nano-sized particles of collagen II by using a high voltage electrostatic field system. The preliminary results showed that the collagen II particles exhibited good sphericity and the particles diameters increased after longer electric field treatment. They were in the range of 208 plusmn 27, 277 plusmn 26 and 467 plusmn 35 nm in diameter at the treatment...
Wavelet entropy (WE), a new method of complexity measure for non-stationary signals, was used to investigate the dynamic features of rat EEGs under three vigilance states. The EEGs of the freely moving rats were recorded with implanted electrodes and were decomposed into four components of delta, theta, alpha and beta by using multi-resolution wavelet transform. Then, the wavelet entropy curves were...
Intensity inhomogeneity in MR images is an undesired phenomenon, which often hampers different steps of quantitative analysis such as segmentation or registration. In this paper we propose a novel fully automated method for retrospective correction of intensity inhomogeneity. The basic assumption is that inhomogeneity correction could be improved by combining the information from multiple MR channels...
In the process of speech recognition, it is especially crucial to precisely locate endpoints of the input utterance to be free of non-speech regions. This paper proposes a novel approach that finds robust features for endpoint detection in a noisy environment. In this proposed method, we integrate both time-frequency enhancement and the spectral entropy feature. Firstly, the noisy speech is enhanced...
Salient or interest points ot a medical image can represent local properties of it. In this paper, a salient points based approach for medical image retrieval is proposed. In order to extract salient points from a medical image, we proposed a novel approach based on spectrum energy variation. Moreover, the other two salient points algorithm are also used. One is entropy-based and the other is a saliency-based...
Diagnostic ultrasound is one of useful and noninvasive tools for clinical medicine. However, due to its qualitative, subjective and experience-based nature, ultrasound images can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features of fractal dimension and the entropies of...
A global optimization technique for image registration using the concept of nonlinear correlation information entropy (NCIE) as the matching criterion is presented. The method makes it possible to efficiently overcome the local minima problem utilizing the extremum property of NCIE. Furthermore, the improved downhill simplex algorithm incorporated variant accuracy tolerance can reduce the evaluation...
This paper introduces an entropy based method for beat to beat classification of long electrocardiograms (ECGs). A state vector is reconstructed using Taken's delay coordinates method and Shannon entropies are calculated for each beat to form feature vectors. Hierarchical clustering is applied to these vectors to classify the beats. The algorithm was used for detection of atrial premature beats and...
We are involved in a comprehensive program to characterize atherosclerotic disease using multiple MR images having different contrast mechanisms (T1W, T2W, PDW, magnetization transfer, etc.) of human carotid and animal model arteries. We use specially designed intravascular and surface array coils that give high signal-to-noise but suffer from sensitivity inhomogeneity and significant noise. We present...
The SPECT imaging process has two fundamental stages: detection and display. The detection stage can be rigorously quantitatively described by Shannon's information theory. Information is transferred from the source to the detector in the photon emitting process. In the detection stage, integrity of projection data can be assessed by the information entropy, which is the conditional entropy standing...
A major focus of implantable cardioverter defibrillator (ICD) research has been to reduce the defibrillation shock energy to prolong battery life and provide an enhanced quality of life for the patient. We investigated whether the degree of disorganization (complexity) of the electrogram is correlated with defibrillation shock outcome. The study data sets were recorded using the high voltage leads...
This paper discusses several important factors which can influence the accuracy of the results obtained from application of the well-known approximate entropy (ApEn) method and the more recently developed sample entropy (SampEn) method to fast neurophysiological signals. Based on the performance of these methods on both computer simulation and experimental data, parameter selection criteria are suggested...
In order to improve the communication rates of brain-computer interface(BCI's), scientists are developing appropriate signal processing methods to extract the user's messages and commands from electroencephalograph (EEG). A fast fixed-point algorithm for independent component analysis(FastICA), possesses the advantages of simply structure and fast computation. However, in some cases, many signals...
We describe the use of directional entropy (DE) in the directional analysis of diffusion tensor imaging (DTI) data. The directional entropy is a measure of disorder in a directional distribution. It could provide a relatively simple, yet meaningful measure about the brain white matter integrity, complementary to the traditional measures used, such as mean diffusivity or indices of diffusion anisotropy...
Heart is one of the most complex dynamic system. Indeed, ECG is important information which reflect the active states of heart. In this paper, select 24 data files of ECG from MIT-BIH database and divide these data into four groups. Series of R-peaks and RR- intervals extracted from these electrocardiograms are analyzed with the correlation dimension and correlation entropy. The results showed that...
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