Electrophysiological auditory responses and language development in infants with periventricular leukomalacia.

This study presents evidence suggesting that electrophysiological responses to language-related auditory stimuli recorded at 46weeks postconceptional age (PCA) are associated with language development, particularly in infants with periventricular leukomalacia (PVL). In order to investigate this hypothesis, electrophysiological responses to a set of auditory stimuli consisting of series of syllables and tones were recorded from a population of infants with PVL at 46weeks PCA. A communicative development inventory (i.e., parent report) was applied to this population during a follow-up study performed at 14months of age. The results of this later test were analyzed with a statistical clustering procedure, which resulted in two well-defined groups identified as the high-score (HS) and low-score (LS) groups. The event-induced power of the EEG data recorded at 46weeks PCA was analyzed using a dimensionality reduction approach, resulting in a new set of descriptive variables. The LS and HS groups formed well-separated clusters in the space spanned by these descriptive variables, which can therefore be used to predict whether a new subject will belong to either of these groups. A predictive classification rate of 80% was obtained by using a linear classifier that was trained with a leave-one-out cross-validation technique.

Local adaptable quadrature filters to demodulate single fringe patterns with closed fringes.

We propose a new approach to demodulate a single fringe pattern with closed fringes by using Local Adaptable Quadrature Filters (LAQF). Quadrature filters have been widely used to demodulate complete image interferograms with carrier frequency. However, in this paper, we propose the use of quadrature filters locally, assuming that the phase is locally quasimonochromatic, since quadrature filters are not capable to demodulate image interferograms with closed fringes. The idea, in this paper, is to demodulate the fringe pattern with closed fringes sequentially, using a fringe following scanning strategy. In particular we use linear robust quadrature filters to obtain a fast and robust demodulation method for single fringe pattern images with closed fringes. The proposed LAQF method does not require a previous fringe pattern normalization. Some tests with experimental interferograms are shown to see the performance of the method along with comparisons to its closest competitor, which is the Regularized Phase Tracker (RPT), and we will see that this method is tolerant to higher levels of noise.

Path independent demodulation method for single image interferograms with closed fringes within the function space C(2).

In the last few years, works have been published about demodulating Single Fringe Pattern Images (SFPI) with closed fringes. The two best known methods are the regularized phase tracker (RPT), and the two-dimensional Hilbert Transform method (2D-HT). In both cases, the demodulation success depends strongly on the path followed to obtain the expected estimation. Therefore, both RPT and 2D-HT are path dependent methods. In this paper, we show a novel method to demodulate SFPI with closed fringes which follow arbitrary sequential paths. Through the work presented here, we introduce a new technique to demodulate SFPI with estimations within the function space C(2); in other words, estimations where the phase curvature is continuous. The technique developed here, uses a frequency estimator which searches into a frequency discrete set. It uses a second order potential regularizer to force the demodulation system to look into the function space C(2). The obtained estimator is a fast demodulator system for normalized SFPI with closed fringes. Some tests to demodulate SFPI with closed fringes using this technique following arbitrary paths are presented. The results are compared to those from RPT technique. Finally, an experimental normalized interferogram is demodulated with the herein suggested technique.

Adaptive monogenic filtering and normalization of ESPI fringe patterns.

A technique is presented for filtering and normalizing noisy fringe patterns, which may include closed fringes, so that single-frame demodulation schemes may be successfully applied. It is based on the construction of an adaptive filter as a linear combination of the responses of a set of isotropic bandpass filters. The space-varying coefficients are proportional to the envelope of the response of each filter, which in turn is computed by using the corresponding monogenic image [Felsberg and Sommer, IEEE Trans. Signal Process. 49, 3136 (2001)]. Some examples of demodulation of real Electronic Speckle Pattern Interferometry (ESPI) images patterns are presented.

An accurate and efficient bayesian method for automatic segmentation of brain MRI.

Automatic three-dimensional (3-D) segmentation of the brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of attention lately. Of the techniques reported in the literature, very few are fully automatic. In this paper, we present an efficient and accurate, fully automatic 3-D segmentation procedure for brain MR scans. It has several salient features; namely, the following. 1) Instead of a single multiplicative bias field that affects all tissue intensities, separate parametric smooth models are used for the intensity of each class. 2) A brain atlas is used in conjunction with a robust registration procedure to find a nonrigid transformation that maps the standard brain to the specimen to be segmented. This transformation is then used to: segment the brain from nonbrain tissue; compute prior probabilities for each class at each voxel location and find an appropriate automatic initialization. 3) Finally, a novel algorithm is presented which is a variant of the expectation-maximization procedure, that incorporates a fast and accurate way to find optimal segmentations, given the intensity models along with the spatial coherence assumption. Experimental results with both synthetic and real data are included, as well as comparisons of the performance of our algorithm with that of other published methods.

Local frequency representations for robust multimodal image registration.

Automatic registration of multimodal images involves algorithmically estimating the coordinate transformation required to align the data sets. Most existing methods in the literature are unable to cope with registration of image pairs with large nonoverlapping field of view (FOV). We propose a robust algorithm, based on matching dominant local frequency image representations, which can cope with image pairs with large nonoverlapping FOV. The local frequency representation naturally allows for processing the data at different scales/resolutions, a very desirable property from a computational efficiency view point. Our algorithm involves minimizing-over all rigid/affine transformations--the integral of the squared error (ISE or L2 E) between a Gaussian model of the residual and its true density function. The residual here refers to the difference between the local frequency representations of the transformed (by an unknown transformation) source and target data. We present implementation results for image data sets, which are misaligned magnetic resonance (MR) brain scans obtained using different image acquisition protocols as well as misaligned MR-computed tomography scans. We experimently show that our L2E-based scheme yields better accuracy over the normalized mutual information.

Robust spatiotemporal quadrature filter for multiphase stepping.

A robust algorithm for phase recovery from multi-phase-stepping images is presented. This algorithm is based on the minimization of an energy (cost) functional and is equivalent to the simultaneous application of a fixed temporal quadrature filter and a spatial adaptive quadrature filter to the phase-stepping pattern ensemble. The algorithm, believed to be new, is specially suited for those applications in which a large number of phase-stepping images may be obtained, e.g., profilometry with a computer-controlled fringe projector. We discuss the selection of parameter values and present examples of its performance in both synthetic and real image sequences.

Piecewise smooth phase reconstruction.

A well-founded and computationally fast method is presented for filtering and interpolating noisy and discontinuous wrapped phase fields that preserves both the 2pi discontinuities that come from the wrapping effect and the true discontinuities that may be present. It also permits the incorporation of an associated quality map, if it is available, in a natural way. Examples of its application to the computation of the isoclinic phase from photoelastic data and to the recovery of discontinuous phase fields from speckle interferometry are presented.

Regularization methods for processing fringe-pattern images.

A powerful technique for processing fringe-pattern images is based on Bayesian estimation theory with prior Markov random-field models. In this approach the solution of a processing problem is characterized as the minimizer of a cost function with terms that specify that the solution should be compatible with the available observations and terms that impose certain (prior) constraints on the solution. We show that, by the appropriate choice of these terms, one can use this approach in almost every processing step for accurate and robust interferogram demodulation and phase unwrapping.

Phase unwrapping through demodulation by use of the regularized phase-tracking technique.

Most interferogram demodulation techniques give the detected phase wrapped owing to the arctangent function involved in the final step of the demodulation process. To obtain a continuous detected phase, an unwrapping process must be performed. Here we propose a phase-unwrapping technique based on a regularized phase-tracking (RPT) system. Phase unwrapping is achieved in two steps. First, we obtain two phase-shifted fringe patterns from the demodulated wrapped phase (the sine and the cosine), then demodulate them by using the RPT technique. In the RPT technique the unwrapping process is achieved simultaneously with the demodulation process so that the final goal of unwrapping is therefore achieved. The RPT method for unwrapping the phase is compared with the technique of least-squares integration of wrapped phase differences to outline the substantial noise robustness of the RPT technique.

Direct ray aberration estimation in Hartmanngrams by use of a regularized phase-tracking system.

The Hartmann test is a well-known technique for testing large telescope mirrors. The Hartmann technique samples the wave front under analysis by use of a screen of uniformly spaced array of holes located at the pupil plane. The traditional technique used to gather quantitative data requires the measurement of the centroid of these holes as imaged near the paraxial focus. The deviation from its unaberrated uniform position is proportional to the slope of the wave-front asphericity. The centroid estimation is normally done manually with the aid of a microscope or a densitometer; however, newer automatic fringe-processing techniques that use the synchronous detection technique or the Fourier phase-estimation method may also be used. Here we propose a new technique based on a regularized phase-tracking (RPT) system to detect the transverse aberration in Hartmanngrams in a direct way. That is, it takes the dotted pattern of the Hartmanngram as input, and as output the RPT system gives the unwrapped transverse ray aberration in just one step. Our RPT is compared with the synchronous and the Fourier methods, which may be regarded as its closest competitors.

Adaptive quadrature filters for multiple phase-stepping images.

We present a new technique for the recovery of local phase from multiple phase-stepping fringe images that uses adaptive quadrature filters constructed by use of Bayesian estimation theory and complex-valued Markov random fields as prior models. It is shown that with this technique it is possible to perform accurate phase reconstructions even for extremely noisy fringe images and that the performance of this technique is nearly independent of the particular noise model, as long as the noise spectrum is wideband.

Phase unwrapping with a regularized phase-tracking system.

We develop a regularized phase-tracking (RPT) technique tounwrap phase maps. The phase maps that can be unwrapped with thisnew method may be bounded by arbitrarily shaped boundaries. Moreover, the RPT unwrapper has a higher noise robustness than previously reported phase-unwrapping schemes.

Demodulation of a single interferogram by use of a two-dimensional regularized phase-tracking technique.

We present a two-dimensional regularized phase-tracking technique that is capable of demodulating a single fringe pattern with either open or closed fringes. The proposed regularized phase-tracking system gives the detected phase continuously so that no further unwrapping is needed over the detected phase.

Fast algorithm for integrating inconsistent gradient fields.

A discrete Fourier transform (DFT) based algorithm for solving a quadratic cost functional is proposed; this regularized functional allows one to obtain a consistent gradient field from an inconsistent one. The calculated consistent gradient may then be integrated by use of simple methods. The technique is presented in the context of the phase-unwrapping problem; however, it may be applied to other problems, such as shapes from shading (a robot-vision technique) when inconsistent gradient fields with irregular domains are obtained. The regularized functional introduced here has advantages over existing techniques; in particular, it is able to manage complex irregular domains and to interpolate over regions with invalid data without any smoothness assumptions over the rest of the lattice, so that the estimation error is reduced. Furthermore, there are no free parameters to adjust. The DFT is used to compute a preconditioner because there is highly efficient hardware to perform the calculations and also because it may be computed by optical means.

Robust procedure for fringe analysis.

A robust procedure for analyzing fringe patterns obtained from speckle interferometric techniques is proposed. The fringes generally are observed only in a region S of a rectangular lattice L. We give a method for computing (from S) the region R, where the unwrapped phase is to be computed; this computation is done by use of a morphological filter (in particular, a closing filter). We then use a fast-unwrapping algorithm to compute the phase: a preconditioned conjugate-gradient algorithm that uses the discrete Fourier transform.

Wave-front recovery from two orthogonal sheared interferograms.

We present a new technique for using the information of two orthogonal lateral-shear interferograms to estimate an aspheric wave front. The wave-front estimation from sheared inteferometric data may be considered an ill-posed problem in the sense of Hadamard. We apply Thikonov regularization theory to estimate the wave front that has produced the lateral sheared interferograms as the minimizer of a positive definite-quadratic cost functional. The introduction of the regularization term permits one to find a well-defined and stable solution to the inverse shearing problem over the wave-front aperture as well as to reduce wave-front noise as desired.

Measure fields for function approximation.

The computation of a piecewise smooth function that approximates a finite set of data points may be decomposed into two decoupled tasks: 1) the computation of the locally smooth models, and hence, the segmentation of the data into classes that consist of the sets of points best approximated by each model; 2) the computation of the normalized discriminant functions for each induced class (which maybe interpreted as relative probabilities). The approximating function may then be computed as the optimal estimator with respect to this measure field. For the first step, we propose a scheme that involves both robust regression and spatial localization using Gaussian windows. The discriminant functions are obtained fitting Gaussian mixture models for the data distribution inside each class. We give an efficient procedure for effecting both computations and for the determination of the optimal number of components. Examples of the application of this scheme to image filtering, surface reconstruction and time series prediction are presented.