Ultrasound (US) imaging deals with forming a brightness image from the amplified backscatter echo when an ultrasound wave is triggered at the region of interest. Imaging artifacts and speckles occur in the image as a consequence of backscattering and subsequent amplification. We demonstrate the usefulness of speckle-related pixels and imaging artifacts as sources of information to perform multiorgan segmentation in US images of the thyroid gland. The speckle-related pixels are clustered based on a similarity constraint to quantize the image. The quantization results are used to locate useful anatomical landmarks that aid the detection of multiple organs in the image, which are the thyroid gland, the carotid artery, the muscles, and the trachea. The spatial locations of the carotid artery and the trachea are used to estimate the boundaries of the thyroid gland in transverse US scans. Experiments performed on a multivendor dataset yield good quality segmentation results with probabilistic Rand index > 0.83 and boundary error 1 mm, and an average accuracy greater than 94%. Analysis of the results using the Dice coefficient as the metric shows that the proposed method performs better than the state-of-the-art methods. Further, experiments conducted on 971 images of a publicly available dataset prove the effectiveness of the algorithm to track the carotid artery for guided interventions. In addition to US-guided interventions, the algorithm can be used as a general framework in applications pertaining to volumetric analysis and computer-aided diagnosis.

We consider the problem of carotid artery segmentation and develop an automated outlining technique based on the active disc formalism that we recently introduced. The outlining problem is posed as one of optimization of a locally defined contrast function with respect to the affine transformation parameters that characterize the active disc. It turns out that standard techniques based on gradient-descent minimization can be used to carry out the optimization, although more sophisticated optimizers could also be deployed. For the initialization, we use a matched filter with a template size chosen based on an estimate of the average size of the carotid artery. We report results of experimental validation on Brno university's signal processing (SP) lab database, which contains 971 transverse mode ultrasound images of the carotid artery. The images in the database are manually annotated using a circle with center and radius explicitly specified in pixels, which serves as the reference. The circular annotation is also a good match with the active disc template considered in this paper. The proposed method results in an average detection accuracy of 95.5% and an average Dice similarity measure of 87.36% and takes only a few seconds of processing time per image. Comparisons with other state-of-the-art techniques are also reported.

Signal quality assessment is an important issue as noisy channels could mean lost information and unreliable data. In the field of Electrocardiograms (ECG), this is also important as noise could affect the detection of transient cardiac conditions which occur in these noisy channels. In VPW-FRI, the common annihilator is used to decompose multichannel signals with common root locations. Using information from the common annihilating filter, this paper will show that poor quality or noisy signals can be classified from the noiseless signals. This is done through the fact that each channel contributes to the solution of a pulse location and the channels which contribute below a certain threshold are deemed to be noisy or of poor quality. We will show that our algorithm works to the point where VPW-FRI is able to distinguish the features of the signal well despite any noise present.

Fetal Electrocardiograms (fECG) are an inexpensive and noninvasive method to determine the heart rate (HR) of the fetus. Large variations in the fetal HR is a good indicator that the fetus is in distress thus allowing for clinical intervention. Although advances have been made in the field of fetal HR detection, more can be done to improve accuracy and efficiency. The Variable Pulse Width - Finite Rate of Innovation (VPW-FRI) method is a suitable method given it deals with pulse parameters such as location, width and amplitude. This allows it to automatically segment and identify the foetal QRS complexes and R peak locations from compressed samples which in turn would yield the fetal HR. Our method, which includes model based denoising and multichannel capability, is comparable to other methods involving machine learning, wavelets and ICA.

Contrary to the popular belief of treating speckle related pixels as noise and filtering an ultrasound image for speckle noise removal, the practical importance and use of these pixels in performing a multi-organ segmentation of the thyroid gland is studied in this research work. In this work, speckle related pixels are classified into three echogenic levels and then used to segment an ultrasound image of the thyroid gland into the trachea, carotid, muscles and thyroid. Novel techniques are introduced to estimate the anterior boundaries of the thyroid gland using low pass filtered intensity gradients of the hyperechoic speckle pixels in transverse and longitudinal ultrasound scans, respectively. An energy functional similar to active contour models is defined to segment that carotid artery using hypoechoic speckle pixels. The proposed technique was executed on 88 images of the thyroid gland. Clinical significance of using speckles to segment is determined by validating on 32 images of the thyroid gland by measuring the overlap with the Ground Truth segmentation obtained from two expert doctors using Dice coefficient as the overlap measure.

Voice impersonators possess a flexible voice which allows them to imitate and create different voice identities. These impersonations present a challenge for forensic analysis and speaker identification systems. To better understand the phenomena underlying successful voice impersonation, we collected a database of synchronous speech and ElectroGlottoGraphic (EGG) signals from three voice impersonators each producing nine distinct voice identities. We analyzed glottal and vocal tract measures including F0, speech rate, vowel formant frequencies, and timing characteristics of the vocal folds. Our analysis confirmed that the impersonators modulated all four parameters in producing the voices, and provides a lower bound on the scale of variability that is available to impersonators. Importantly, vowel formant differences across voices were highly dependent on vowel category, showing that such effects cannot be captured by global transformations that ignore the linguistic parse. We address this issue through the development of a no-reference objective metric based on the vowel-dependent variance of the formants associated with each voice. This metric both ranks the impersonators natural voices highly, and correlates strongly with the results of a subjective listening test. Together, these results demonstrate the utility of voice variability data for the development of voice disguise detection and speaker identification applications.

Parametric signals that have a finite number of degrees of freedom per unit of time are defined as signals with Finite Rate of Innovation (FRI). Sampling and reconstruction schemes have been developed based on the 1D FRI principle and applied to reconstructing step edge images on a row by row basis. In this paper, we derive the 2D FRI principle by exploiting the separability of the B-spline sampling kernel. The proposed 2D FRI principle regards the sampling and reconstruction as block by block operations. The step-edge parameters can be retrieved in high accuracy with no post-processing. The performance on synthetic images shows that our proposed technique is more precise than the row by row approaches on Signal-to-Noise Ratio (SNR) levels larger than 4 dB. Experimental results on real images demonstrate that the proposed method can reconstruct the step-edge precisely under noisy and practical sampling conditions.

Voice impersonators possess a flexible voice and thus can change their voice identity. They are able to imitate various people and characters which differ in age, gender, accent and voice quality. State of the art electronic voice conversion systems are not able to successfully mimic their human counterparts as they lack naturalness. To understand why human impersonators are successful and what parameters they rely on to change their voice, we analyze nine voices produced by a professional voice impersonator. We compute different acoustical measures and discuss their linguistic implications. The acoustical measures include pitch, speech rate and formant frequencies. Our results show that differences in the voice identity features such as age and gender are reflected in the acoustic parameters of the impersonations. The analysis is distinguished from previous studies on impersonators in giving full consideration to voice identity features.

Sampling theory for continuous time signals which have a bandlimited representation in fractional Fourier transform (FrFT) domain-a transformation which generalizes the conventional Fourier transform-has blossomed in the recent past. The mechanistic principles behind Shannon's sampling theorem for fractional bandlimited (or fractional Fourier bandlimited) signals are the same as for the Fourier domain case i.e. sampling (and reconstruction) in FrFT domain can be seen as an orthogonal projection of a signal onto a subspace of fractional bandlimited signals. As neat as this extension of Shannon's framework is, it inherits the same fundamental limitation that is prevalent in the Fourier regime-what happens if the signals have singularities in the time domain (or the signal has a nonbandlimited spectrum)? In this paper, we propose a uniform sampling and reconstruction scheme for a class of signals which are nonbandlimited in FrFT sense. Specifically, we assume that samples of a smoothed version of a periodic stream of Diracs (which is sparse in time-domain) are accessible. In its parametric form, this signal has a finite number of degrees of freedom per unit time. Based on the representation of this signal in FrFT domain, we derive conditions under which exact recovery of parameters of the signal is possible. Knowledge of these parameters leads to exact reconstruction of the original signal.

Fractional delay filters (FDFs) play an important role in certain areas of digital signal processing and communication engineering, where it is desirable to generate delays that are of the order of a fraction of the sampling period. In this paper, we advocate the use of generalized cardinal exponential splines-a class of compactly supported functions that is much richer than the existing B-spline family-for designing precision FDFs. One advantage of using generalized cardinal exponential splines is that it provides ready access to several spline families and other kernels which could be used for FDF design. The B-spline and Lagrange interpolator based FDFs are a special case of our proposition. We also discuss a design example and show that it is possible to design filters that have lower interpolation errors as compared to its B-spline counterparts.

Analyses of neonatal EEG seizures and subsequent diagnoses can only be done effectively on long-term recordings on the condition that the morphology of the EEG signals are retained. Therefore, a reliable, accurate and efficient compression and reconstruction technique is necessary to store and retrieve the data. In this paper, we propose a new compression technique for neonatal EEG seizure signals via sampling theory developed for signals with a finite rate of innovation. Firstly, the EEG seizure signals are modeled as periodic nonuniform linear splines. Next, through the sampling and reconstruction scheme developed for signals with finite rate of innovation, we show that neonatal EEG seizure signals can be highly compressed while preserving their morphologies.

In this paper, a new fragile watermarking method for digital image authentication is proposed based on the zero locations of the z-transform. The z-transform domain is a new transform space for fragile watermark embedding. Our watermarking method is designed by exploiting the sensitivity of the positions of the zeroes of the z-transform around the unit circle to any change made on the host image. The watermarking system can localize the portions of a watermarked image that have been tampered with with high accuracy. In addition, the newly proposed scheme is more secure than normal least-significant bits-based fragile watermarking techniques. Experimental results as well as the theoretical analysis demonstrated the fragility and accuracy of the new method.

A case study on reproducible research in sampling theory of signals containing a finite rate of innovation is the topic of this paper. By building a solid research which is furthermore reproducible enables the researcher to build intuition in a research area and to progress at a much faster pace. Here, we show that the founding problem of sampling and exact reconstruction of periodic streams of Dirac pulse will be the basis of the sampling theory for signals with finite rate of innovation. The sampling theory can be extended to other signals such as piecewise polynomials, bandlimited signals with additive shot noise and the sum of bandlimited signals with piecewise polynomial signals. It is shown that the implementation is based on the one for streams of Dirac pulses, thus making the new research reproducible as well.

In this correspondence, we consider sampling continuous-time periodic bandlimited signals which contain additive shot noise. The classical sampling scheme does not perfectly recover these particular nonbandlimited signals but only reconstructs a lowpass filtered approximation. By modeling the shot noise as a stream of Dirac pulses, we first show that the sum of a bandlimited signal with a stream of Dirac pulses falls into the class of signals that contain a finite rate of innovation, that is, a finite number of degrees of freedom. Second, by taking into account the degrees of freedom of the bandlimited signal in the sampling and reconstruction scheme developed previously for streams of Dirac pulses, we derive a sampling and perfect reconstruction scheme for the bandlimited signal with additive shot noise.

Data embedding in sharply-contrasted binary images like text, drawing, signature and cartoon is a challenging issue due to simple pixel statistics in such images. Arbitrary modification to the pixels can be visually perceptible in the process of data embedding. The use of a valid perceptual model is important to minimize the effect of such visual distortion in binary images. In this paper, a novel perceptual model is used to embed significant amount of information such that the original and the marked images before and after data embedding process are perceptually similar. In our model, the distortion that occurs after flipping a pixel is estimated on the curvature-weighted distance difference (CWDD) measure between two contour segments.

We present a no-reference blur metric for images and video. The blur metric is based on the analysis of the spread of the edges in an image. Its perceptual significance is validated through subjective experiments. The novel metric is near real-time, has low computational complexity and is shown to perform well over a range of image content. Potential applications include optimization of source coding, network resource management and autofocus of an image capturing device.

We consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, piecewise polynomials. We demonstrate that by using an adequate sampling kernel and a sampling rate greater or equal to the number of degrees of freedom per unit of time, one can uniquely reconstruct such signals. This proves a sampling theorem for a wide class of signals beyond bandlimited signals. Applications of this sampling theorem can be found in signal processing, communication systems and biological systems. 1.

This paper is concerned with finding the locations of an irregularly sampled finite discrete-time band-limited signal. First a geometrical approach is described and is transformed into an optimization problem. Due to the structure of the problem, multiple solutions exist and are shifts of each other. Three methods of solution are suggested: an exhaustive method which finds the exact set of locations; random search method and cyclic coordinate method, both descent methods, which find approximate or exact solutions. The cyclic coordinate method is less likely to fall in a local minimum and proves to be more satisfactory than the random search method in the presence of jitter. A practical example, where a signal is sampled several times with a regular spacing, is also described.