Segmentation is an essential task in ultrasound image analysis. Recently, the trend in literature is towards incorporation of high-level information, e.g., shape priors, since many low-level segmentation techniques suffer from the characteristics of medical ultrasound images, i.e., speckle noise, scattering artifacts, and shadowing effects. However, the majority of these works implicitly assume...

In this paper we propose an anisotropic model for 2D fractional noise generated from a Gaussian mixture distribution. We propose two identification methods for this model: the first one is a forward modeling approach based on even order cumulants of the field, while the second one is an inverse modeling approach where the synthesis filter is inverted in order to obtain an estimation of the driv...

We describe an eeective approach to object or feature detection in point patterns via noise modeling. This is based on use of a redundant or non-pyramidal wavelet transform. Noise modeling is based on a Poisson process. We illustrate this new method with a range of examples. We use the close relationship between image (pixelated) and point representations to achieve the result of a clustering m...

In this paper, we introduce improvements to previous sines + transients + noise audio modeling systems, including new sinusoidal trajectory selection and quantization procedures. In previous work [1], the audio is first segmented into transient and non-transient regions. The transient region is modeled using traditional transform coding techniques, while the non-transient regions are modeled us...

| In this tutorial paper, we review fundamentals of oscillator phase noise emphasizing its physical picture based on the concept of phase di®usion. This review is intended to provide an essential understanding of phase noise rather than a comprehensive phase noise modeling. We then summarize several phase noise reduction techniques for various types of oscillators. Index Terms|oscillators, phas...

This paper presents a technique to estimate the noise due to electromagnetic waves emitted from electrical appliances working nearby the digital communication system and study their impact towards digital communication systems by using the amplitude probability distribution (APD). A unique noise APD pattern is obtained from each measurement of noise due to electromagnetic induction from electri...

We propose a new multiresolution variational joint denoising/deblurring approach, involving a priori assumptions on the solution and knowledge of the imaging systems to account for effects due to acquisition noise (edge preservation, degradation noise modeling, bounded noise assumption and spectral control of noise level whiteness and stationarity). The techniques used are drawn from a variety ...

An integrated approach for estimation and reduction of measurement variation (and its components) through a single parameter design experiment is developed. Systems with a linear signal-response relationship are considered. The noise factors are classified into a few distinct categories based on their impact on the measurement system. A random coefficients model that accounts for the effect of ...

This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We use multidimensional Gaussian distribution to analyze the separation of different class samples in a training data set, and then generate artificial noise samples in the training set using a noise modeling algorithm. The noise analysis allows us to ident...