Guided wave expansion in warped curvelet frames.

Lamb wave testing for structural health monitoring (SHM) often relies on analysis of wavefields recorded through scanning laser Doppler vibrometers (SLDVs) or ultrasonic scanners. Damage detection and characterization with these techniques requires isolation of defect-induced reflections in the wavefield from the injected wave packet and from scattering events associated with structural features such as boundaries, rivets, joints, etc. This is a challenging task when dealing with complex structures and multimodal, dispersive propagation regimes, whereby various wave contributions in both the time/space and the frequency/wavenumber domain overlap. A new mathematical tool named warped curvelet frames (WCFs) is proposed to effectively decompose the recorded wavefields. The presented technique results from the combination of two operators, i.e., the curvelet transform (CT) and the warped frequency transform (WFT). The CT provides an optimally sparse representation of nondispersive wave propagators. Combining the CT with the WFT allows for a flexible analysis of multimodal wave propagation in dispersive media. Exploiting the spatial and temporal localization of curvelets, as well as the spectro-temporal adaptation of the analysis frame to the characteristics of each propagating mode, provided by frequency warping, a convenient decomposition of guided waves is achieved and relevant contributions can be effectively isolated. The proposed approach is validated through dedicated simulations and further tested experimentally to demonstrate the effectiveness of the method in separating guided wave modes corresponding to acoustic events in close spatial proximity.

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 l(2)-norm or (1)-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 l(1)-norm deconvolution techniques attests to the superiority of the proposed algorithm.

Double-channel, frequency-steered acoustic transducer with 2-D imaging capabilities.

A frequency-steerable acoustic transducer (FSAT) is employed for imaging of damage in plates through guided wave inspection. The FSAT is a shaped array with a spatial distribution that defines a spiral in wavenumber space. Its resulting frequency-dependent directional properties allow beam steering to be performed by a single two-channel device, which can be used for the imaging of a two-dimensional half-plane. Ad hoc signal processing algorithms are developed and applied to the localization of acoustic sources and scatterers when FSAT arrays are used as part of pitch-catch and pulse-echo configurations. Localization schemes rely on the spectrogram analysis of received signals upon dispersion compensation through frequency warping and the application of the frequency-angle map characteristic of FSAT. The effectiveness of FSAT designs and associated imaging schemes are demonstrated through numerical simulations and experiments. Preliminary experimental validation is performed by forming a discrete array through the points of the measurement grid of a scanning laser Doppler vibrometer. The presented results demonstrate the frequency-dependent directionality of the spiral FSAT and suggest its application for frequency-selective acoustic sensors, for the localization of broadband acoustic events, or for the directional generation of Lamb waves for active interrogation of structural health.

Warped basis pursuit for damage detection using lamb waves.

This paper presents a novel time-frequency procedure based on the warped frequency transform (WFT) to process multi-mode and dispersive Lamb waves for structural health monitoring (SHM) applications. The proposed signal processing technique is applied to time waveforms recorded at an array of scan points after waveguide excitation. The WFT is combined with a basis pursuit algorithm to extract the distance traveled by the ultrasonic waves even in the case of multi-modal dispersive propagation associated with broadband excitation of the waveguide. This is obtained through a decomposition of the acquired signals using dictionaries composed by optimized atomic functions which are designed to match the spectro-temporal structure of the various propagating modes. The warped basis pursuit (W-BP) analysis of several acquired waveforms results in distance signals that can be combined through classical beamforming techniques for acoustical source imaging purposes. A masking procedure is also proposed to suppress imaging noise. This approach is tested on experimental data obtained by broadband guided wave excitation in a 1-mm-thick aluminum plate with an artificially introduced through crack and tiny holes, followed by multiple waveguide displacement recording through a scanning laser Doppler vibrometer. Dispersion compensation, high-resolution source, and defect imaging are demonstrated even in domain regions that are not directly accessible for measurement.

A retrospective study to reduce prostate biopsy cores by a real time interactive tool.

OBJECTIVE: Prostate carcinoma (PCa) is one of the most frequent neoplasms, with more than 110.000 new cases/year in Europe. As PCa is not clearly demonstrable at transrectal ultrasound (TRUS), guidelines on TRUS guided biopsy suggest to perform a random tissue sampling (at least 8-12 "cores" depending on gland volume). Although accuracy grows with core number, patient discomfort and adverse event probability grow as well. Thus it would be worth to aim to reduce the number of prostate biopsy cores without loss of diagnostic accuracy. MATERIALS AND METHODS: A retrospective study was performed to evaluate the feasibility of an improved version of a rtCAB tool developed at DEIS (University of Bologna) for the reduction of prostate biopsy cores. rtCAB is an innovative processing technique which enhances TRUS video stream by a live false color overlay image that helps the physician to perform the biopsy by guiding the sampling into target zones. In order to train rtCAB, a monocentric, single operator prostate gland adenocarcinoma database has been built. The database enlists 81 patients, for a total of 743 prostate byoptic (PBx) cores and 14860 ROI. For each patient we collected age, PSA levels, digital rectal examination (DRE) findings, presence or absence of focal lesions, and prostate volume. During TRUS, raw ultrasound data were acquired and associated to each PBx core. For each core we collected both the radio frequency (RF) signal and the histological outcome. RESULTS: The whole system was optimized for reducing the number of false positives while preserving an acceptable number of false negatives. Comparing to a classical PBx approach (8-12 cores), the estimated positive predictive value (PPV) of our method increased from 25% to 40%, with an overall sensitivity of 85%. CONCLUSIONS: Preliminary results show that the proposed tool can provide real-time feedback to the operator during TRUS. Sensitivity and PPV values suggest that a reduction of almost 50% the number of biopsy cores without losing in diagnostic accuracy is feasible. A prospective study is needed to further confirm these preliminary retrospective results.

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.

Ultrasonic guided-waves characterization with warped frequency transforms.

Guided wave (GW) dispersion curves can be extracted from a time-transient measurement by means of timefrequency representations (TFRs). Unfortunately, any TFR is subject to the time-frequency uncertainty principle. This, in general, limits the capability of TFRs to characterize closely spaced guided modes over a wide frequency range. To overcome this limitation, we implemented a new warped frequency transform that presents enhanced mode extraction capabilities because of a more flexible tiling of the time-frequency domain. The tiling is designed to match the dispersive spectro-temporal structure of a GW by selecting an appropriate map of the time-frequency plane. The proposed transformation is fast, invertible, and covariant to group delay shifts. An application to Lamb waves propagating in an aluminum plate is presented. Time-transient GWs propagation events obtained both numerically and experimentally are considered. The results show that the proposed warped frequency transform limits the interference patterns which appear with other TFRs and produces a sparse representation of the Lamb wave pattern that can be suitable for identification and characterization purposes.

A reduced complexity estimation algorithm for ultrasound images de-blurring.

In this paper we propose a deconvolution technique for ultrasound images based on a Maximum Likelihood (ML) estimation procedure. In our approach the ultrasonic radio-frequency (RF) signal is considered as a sequence affected by Intersymbol Interference (ISI) and AWG noise. In order to reduce the computational cost, the estimation is performed with a reduced-state Viterbi algorithm. The channel effect is estimated in two different ways: either measuring the transducer response with an experimental setting or with blind homomorphic techniques. We observed an enhancement in image quality with respect to different metrics. Extensive tests were made to estimate the quantization alphabet that gives the best performances.