A Fast Signal-Dependent Time-Frequency Representation

In last few years, in order to overcome same limitations of the short time Fourier transform (STFT), while avoiding the cross-terms that make the Wigner distribution difficult to interpret, some signal-dependent time-frequency representations (SDTFR) have been proposed. In this paper, the authors introduce a computationally efficient signal-dependent time-frequency method which is suitable for on-line analysis. This SDTFR uses a Gaussian window (GW) similar to STFT, but varies the parameter σ of the GW with time to achieve high signal concentration and high resolution in time. The parameter σ can be automatically calculated by the slope of instantaneous frequency (IF) and instantaneous bandwidth (IB) at that time.published_or_final_versio

Adaptive thresholding by variational method

When using thresholding method to segment an image, a fixed threshold is not suitable if the background is uneven. Here, we propose a new adaptive thresholding method using variational theory. The method requires only one parameter to be selected and the adaptive threshold surface can be found automatically from the original image.published_or_final_versio

Volume Estimation by Wavelet Transform of Doppler Heart Sound During Venous Air-Embolism in Dogs

The Doppler heart sound signals detected by the precordial Doppler ultrasound method under simulated sub clinical and clinically significant venous air embolism were studied in anesthetized dogs. Signal processing using wavelet transform enhanced the contrast of embolic to normal signal, facilitating automatic detection and extraction of embolic signal simply by thresholding. Linear relationship of good correlation coefficient was obtained in log-log scale between the subclinical volume of injected air and the corresponding embolic signal power in all dogs. The calibration curve was found to be good estimate of the volume of embolic air during simulated clinically significant venous air embolism. Hence, we overcame the need of constant human attention for detecting venous air embolism and the lack of quantitative information on the volume of embolic air in the traditional precordial Doppler ultrasound method by the present approach.published_or_final_versio

Fibrillary glomerulonephritis: a case report

Fibrillary glomerulonephritis is a recently recognised condition. The usual presentation is heavy proteinuria. The diagnosis is established by demonstration of the characteristic Congo-red negative, randomly arranged microfibrils in the glomeruli by electron microscopy. At present, there is no proven effective treatment for this condition and the prognosis is generally poor. The first case of fibrillary glomerulonephritis diagnosed in Hong Kong is reported here in a 38-year-old woman.published_or_final_versio

Wavelet analysis of head-related transfer functions

The directional-dependent information in the head-related transfer function (HRTF) is important for the study of human sound localization system and the synthesis of virtual auditory signals. Its time-domain and frequency-domain characteristics have been widely studied by researchers. The purpose of this paper is to explore the ability of discrete wavelet transform to describe the time-scale characteristics of HRTFs. Both the time-domain characteristics and energy distribution of different frequency subbands were studied. Discrete wavelet analysis is found to be a new direction-dependence information showing the relation of the characteristics of the HRTFs to sound source directions.published_or_final_versio

A time domain binaural model based on spatial feature extraction for the head-related transfer function

A complex-valued head-related transfer function (HRTF) can be represented as a real-valued head-related impulse response (HRIR). The interaural time and level cues of HRIRs are extracted to derive the binaural model and also to normalize each measured HRIR. Using the Karhunen–Loeve expansion, normalized HRIRs are modeled as a weighted combination of a set of basis functions in a low-dimensional subspace. The basis functions and the space samples of the weights are obtained from the measured HRIR. A simple linear interpolation algorithm is employed to obtain the modeled binaural HRIRs. The modeled HRIRs are nearly identical to the measured HRIRs from an anesthetized live cat. Typical mean-square errors and cross-correlation coefficients between the 1816 measured and modeled HRIRs are 1% and 0.99, respectively. The real-valued operations and linear interpolating in the model are very effective for speeding up the model computation in real-time implementation. This approach has made it possible to simulate real free-field signals at the two eardrums of a cat via earphones and to study the neuronal responses to such a virtual acoustic space (VAR). ©1997 Acoustical Society of America.published_or_final_versio

A fast deformable region model for brain tumor boundary extraction

We present a modified deformable region model for extraction of a brain tumor boundary in 2D MR images. The deformable region model tolerates a rough initial plan when compared with the active contour model. However, it is time consuming to compute and compare the gray level distribution of the object and all its boundary points. Using a point sampling technique, the number of boundary point processed is greatly reduced. Performance of our modified deformable region model is evaluated on a MR image. The modified model is fast while similar results are obtained.published_or_final_versio

Multi-resolution decomposition applied to crackle detection

Crackles, heard over the lungs in a variety of diseases, are one of the most important physical signs in clinical medicine. They have an explosive pattern in the time domain, with a rapid onset and short duration. The timing, repeatability and shape of crackles are important parameters for diagnosis. Therefore, automatic detection of crackles and their classification as fine and coarse crackles have important clinical value. Since the multi-resolution decomposition technique can give high resolution in both time and frequency, it can be exploited to detect crackles and to classify them according to the information in each scale. In this paper, we present a new method for crackle detection based on the continuous wavelet transform. The theory, methods and experimental results are given in detail in this paper.published_or_final_versio

An adaptive RBF neural network model for evoked potential estimation

A method for evoked potential estimation based on an adaptive radial basis function neural network (RBFNN) model is presented in this paper. During training, the number of hidden nodes (number of RBFs) and model parameters are adjusted to fit the target signal which is obtained by averaging. In order to reduce computational complexity and the influence of noise in estimating single-trial evoked potential (EP), the number of hidden nodes is also minimized in training. After training, both peak latency and amplitude, being distinctive features of an EP, are characterized by center and height of the corresponding RBF respectively. In EP estimation, an adaptive algorithm is employed to track the peaks from trial to trial by adapting the center and height of RBFs directly. The adaptive RBFNN is tested on a computer simulated data set and clinical EP recording. Our proposed algorithm is suitable for tracking EP waveform variations.published_or_final_versio

Design consideration of a multi-function otoacoustic emission measurement system

A new approach for recording otoacoustic emissions (OAEs) is described in the paper. The system is based on a personal computer equipped with INTEL Pentium CPU. A single chip microcomputer INTEL 8096 is developed to be a stimulus generator. Some critical problems and circuit parameters in the design of this system are presented in the paper. The main advantages of the system are (1) it can record three kinds of OAEs which have many clinical applications; (2) it can save raw data for further analysis, as most researchers need; (3) plenty of analysis functions can be developed in this system. With the use of the newly developed system, SOAEs, TEOAEs, and DPOAEs have been successfully measured.published_or_final_versio