L. De Marchi

Ultrasonic guided-waves characterization with Warped Frequency Transforms

In this work a new time-frequency procedure for the extraction of multimodal and dispersive guided waves (GWs) from a recorded time-waveform is presented. The proposed ldquoWarped Frequency Transformrdquo (WFT) is based on a time-frequency domain tiling chosen to match the spectro-temporal structure of the different propagating guided waves by selecting an appropriate warping map which generates non-linearly frequency modulated atoms. The WFT transformation is fast, invertible, covariant to group velocity-delay shifts and, in force of the more flexible tiling, presents enhanced modes extraction capabilities. An application to Lamb Waves propagating in an isotropic plate is presented to show the potential of the proposed procedure.

A passive monitoring technique based on dispersion compensation to locate impacts in plate-like structures

A method for impact location in plate-like structures is proposed. The approach is based on guided waves dispersion compensation. Procedures based on dispersion compensation are usually applied to active monitoring techniques, as they require the knowledge of the time of impact to effectively compensate the guided waves dispersive behaviour. Unfortunately, this knowledge is not given in passive monitoring techniques. Despite this limit, the proposed dispersion compensation procedure is useful as it removes in the group delay of the acquired signals the dependence on the travelled distance. By cross-correlating the signals related to the same event acquired by different sensors, the difference in travelled distances can be determined and used to locate the wave source via hyperbolic positioning. The results show that the developed tool could pave he way for a new class of procedures to locate impacts in waveguides.

Predictive Deconvolution and Hybrid Feature Selection for Computer-Aided Detection of Prostate Cancer

Computer-aided detection (CAD) schemes are decision making support tools, useful to overcome limitations of problematic clinical procedures. Trans-rectal ultrasound image based CAD would be extremely important to support prostate cancer diagnosis. An effective approach to realize a CAD scheme for this purpose is described in this work, employing a multi-feature kernel classification model based on generalized discriminant analysis. The mutual information of feature value and tissue pathological state is used to select features essential for tissue characterization. System-dependent effects are reduced through predictive deconvolution of the acquired radio-frequency signals. A clinical study, performed on ground truth images from biopsy findings, provides a comparison of the classification model applied before and after deconvolution, showing in the latter case a significant gain in accuracy and area under the receiver operating characteristic curve.

A restoration framework for ultrasonic tissue characterization

Ultrasonic tissue characterization has become an area of intensive research. This procedure generally relies on the analysis of the unprocessed echo signal. Because the ultrasound echo is degraded by the non-ideal system point spread function, a deconvolution step could be employed to provide an estimate of the tissue response that could then be exploited for a more accurate characterization. In medical ultrasound, deconvolution is commonly used to increase diagnostic reliability of ultrasound images by improving their contrast and resolution. Most successful algorithms address deconvolution in a maximum a posteriori estimation framework; this typically leads to the solution of ℓ2-norm or ℓ1-norm constrained optimization problems, depending on the choice of the prior distribution. Although these techniques are sufficient to obtain relevant image visual quality improvements, the obtained reflectivity estimates are, however, not appropriate for classification purposes. In this context, we introduce in this paper a maximum a posteriori deconvolution framework expressly derived to improve tissue characterization. The algorithm overcomes limitations associated with standard techniques by using a nonstandard prior model for the tissue response. We present an evaluation of the algorithm performance using both computer simulations and tissue-mimicking phantoms. These studies reveal increased accuracy in the characterization of media with different properties. A comparison with state-of-the-art Wiener and ℓ1-norm deconvolution techniques attests to the superiority of the proposed algorithm.

Fast Computation of Frequency Warping Transforms

In this paper, we introduce an analytical approach for the frequency warping transform. Criteria for the design of operators based on arbitrary warping maps are provided and an algorithm carrying out a fast computation is defined. Such operators can be used to shape the tiling of time-frequency (TF) plane in a flexible way. Moreover, they are designed to be inverted by the application of their adjoint operator. According to the proposed model, the frequency warping transform is computed by considering two additive operators: the first one represents its nonuniform Fourier transform approximation and the second one suppresses aliasing. The first operator is fast computable by various interpolation approaches. A factorization of the second operator is found for arbitrary shaped nonsmooth warping maps. By properly truncating the operators involved in the factorization, the computation turns out to be fast without compromising accuracy.

Comparison of a programmable DSP and FPGA implementation for a wavelet-based denoising algorithm

In this work the authors presented a field programmable gate array (FPGA) and a digital signal processor (DSP) implementations of an algorithm for real-time signal detection and denoising based on undecimated (stationary) wavelet packet transform (SWPT). The performance was compared in terms of operating clock frequencies, power consumption and signal-to-noise-ratio (SNR) due to finite word-length effects using a fixed-point arithmetics in the FPGA and floating-point in DSP. Finally the possibility of reconfiguration and extension is considered

Analytical computation of fast frequency warping

In this work we introduce an analytical characterization of the frequency warping operator of arbitrary shaped non-smooth warping maps. The transformation matrix is decomposed in two additive terms: the first term represents its nonuniform Fourier transform approximation while the second term is imposed for aliasing suppression. The first transformation is known to be analytically characterized and fast computable by an interpolation approach. For the second transformation an analytical representation is introduced which allows a fast computation and a simple design. Finally, an example of a potential application is shown.

Frequency Warping Biorthogonal Frames

Frequency warping is theoretically designed to be a unitary operator of infinite input and output dimensions, thus performing the resolution of identity. In real implementations finite dimensions have to be considered, then perfect reconstruction cannot be fulfilled. The accuracy of reconstruction is particularly compromised in case of non-smooth warping maps, which are more useful for practical applications. In order to overcome this limitation, a new frequency warping biorthogonal frame operator for non-smooth warping maps is introduced in this work. The proposed transformation is based on a mathematical model which has been previously introduced for computational purposes. By adding some redundancy with respect to the truncation of the infinite dimensions operator, the effect of an infinite output dimension can be taken into account in a compressed way, based on an analytical factorization. In the reconstruction process, the additional redundant samples are expanded, thus guaranteeing near perfect reconstruction.

An Accurate Algorithm for Fast Frequency Warping

In this work we present a fast and accurate algorithm to compute frequency warping of arbitrary shaped maps. In contrast to the common Laguerre approach, frequency warping is represented by a matrix of truncated finite dimensions. The transformation matrix is decomposed in two additive terms: the first term represents its nonuniform Fourier transform approximation while the second term is imposed for aliasing suppression. Both matrices are approximated with a least square approach according to a suitable set of vectors. The cardinality of this set is shown to be nearly proportional to the logarithm of the matrix dimension. Finally, trade-off aspects between algorithm complexity and performance are discussed

A new Warped Frequency Transformation (WFT) for Guided Waves characterization

The characterization of the dispersive behaviour of stress guided waves (GWs) from a time transient measurement is generally attempted by means of time-frequency representations (TFRs). Unfortunately, any TFR is subjected to the time-frequency uncertainty principle that limits the capability of the TFR to distinguish multiple, closely spaced guided modes, over a wide frequency range. To this aim we implemented a new Warped Frequency Transform (WFT) that in force of a more flexible tiling of the time-frequency domain presents enhanced modes extraction capabilities. Such tiling, composed by non linearly modulated atoms, is built on the dispersive group velocity curve of a particular propagating mode. The resulting TFR thus emphasizes the energy content associated to that particular guided mode within the recorded time waveform. Here we propose an application of the WFT to numerically simulated Lamb Waves propagating in an aluminum plate. The results show that the proposed WFT limits interference patterns which appears with others TFRs and produces a sparse representation of the dispersive Lamb wave pattern that can be suitable for identification and characterization purposes.