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PubMed2005

Despeckling of medical ultrasound images using data and rate adaptive lossy compression.

A novel technique for despeckling the medical ultrasound images using lossy compression is presented. The logarithm of the input image is first transformed to the multiscale wavelet domain. It is then shown that the subband coefficients of the log-transformed ultrasound image can be successfully modeled using the generalized Laplacian distribution. Based on this modeling, a simple adaptation of the zero-zone and reconstruction levels of the uniform threshold quantizer is proposed in order to achieve simultaneous despeckling and quantization. This adaptation is based on: (1) an estimate of the corrupting speckle noise level in the image; (2) the estimated statistics of the noise-free subband coefficients; and (3) the required compression rate. The Laplacian distribution is considered as a special case of the generalized Laplacian distribution and its efficacy is demonstrated for the problem under consideration. Context-based classification is also applied to the noisy coefficients to enhance the performance of the subband coder. Simulation results using a contrast detail phantom image and several real ultrasound images are presented. To validate the performance of the proposed scheme, comparison with two two-stage schemes, wherein the speckled image is first filtered and then compressed using the state-of-the-art JPEG2000 encoder, is presented. Experimental results show that the proposed scheme works better, both in terms of the signal to noise ratio and the visual quality.

Algorithms↗

PubMed2002

Extraction and modelling of oscillatory potentials.

This paper considers the recommendation that Oscillatory Potentials (OP) be extracted by filtering in the frequency domain. This recommendation presumes that filtering isolates OPs from other ERG waveforms. However, we show that the leading edge of the a-wave has substantial frequency overlap with the OP spectrum at high intensities and that it contaminates these wavelets in the frequency domain. We propose a method of signal conditioning that removes a-waves prior to filtering. When this is done, the OPs show a bimodal distribution in the frequency domain that is well approximated by two Gaussians having means (+/-std. dev.) of 91.0 +/- 14.6 Hz and 153.1 +/- 17.1 Hz. This implies that two functions can be used to model the OPs in the time domain. However, we show that as most of the power of the Fourier spectrum (74%) is contained in a single Gaussian, a reasonable OP model can be derived by using a single function in the time domain. We test such a model on humans (n=5) and pigmented (n=14) and albino (n=14) guinea-pigs and show that it provides excellent fits to data across a range of flash exposures. Furthermore, changes in OP amplitude and timing between strains of guinea-pigs are easily detected with this model. We show that there is no statistical justification for making the model more complex by including multiple functions. Such paramatisation of the OP envelope provides a valuable and intuitive description of the OP waveforms in the time domain. The model provides an excellent description of OPs obtained with the current paradigm, however the single gaussian model may be deficient under stimulus conditions which produce highly asymmetric OP envelopes.

Adult↗

PubMed2006

Time and frequency domain responses of the mechanomyogram and electromyogram during isometric ramp contractions: a comparison of the short-time Fourier and continuous wavelet transforms.

The purposes of this study were to examine the mechanomyographic (MMG) and electromyographic (EMG) time and frequency domain responses of the vastus lateralis (VL) and rectus femoris (RF) muscles during isometric ramp contractions and compare the time-frequency of the MMG and EMG signals generated by the short-time Fourier transform (STFT) and continuous wavelet transform (CWT). Nineteen healthy subjects (mean+/-SD age=24+/-4 years) performed two isometric maximal voluntary contractions (MVCs) before and after completing 2-3, 6-s isometric ramp contractions from 5% to 100% MVC with the right leg extensors. MMG and surface EMG signals were recorded from the VL and RF muscles. Time domains were represented as root mean squared amplitude values, and time-frequency representations were generated using the STFT and CWT. Polynomial regression analyses indicated cubic increases in MMG amplitude, MMG frequency, and EMG frequency, whereas EMG amplitude increased quadratically. From 5% to 24-28% MVC, MMG amplitude remained stable while MMG frequency increased. From 24-28% to 76-78% MVC, MMG amplitude increased rapidly while MMG frequency plateaued. From 76-78% to 100% MVC, MMG amplitude plateaued (VL) or decreased (RF) while MMG frequency increased. EMG amplitude increased while EMG frequency changed only marginally across the force spectrum with no clear deflection points. Overall, these findings suggested that MMG may offer more unique information regarding the interactions between motor unit recruitment and firing rate that control muscle force production during ramp contractions than traditional surface EMG. In addition, although the STFT frequency patterns were more pronounced than the CWT, both algorithms produced similar time-frequency representations for tracking changes in MMG or EMG frequency.

Adult↗

PubMed2005

Cochlear maturation and otoacoustic emissions in preterm infants: a time-frequency approach.

Click-evoked otoacoustic emissions (CEOAEs) from preterm infants were analyzed to characterize developmental changes of cochlear active mechanisms. Due to their strong time-varying properties, CEOAEs were studied with a time-frequency approach--the wavelet transform (WT). By means of the WT, CEOAEs were decomposed into 12 frequency bands, spanning the 0.25-6.25 kHz range. For each band, the root-mean-square (RMS) level and latency were studied as functions of both frequency and age. Because CEOAEs were averaged using the non-linear mode of acquisition, the developmental changes in observed in this study are related to the non-linear component (which is actually the most predominant component of the active cochlear response) of CEOAEs, the linear one being mostly canceled out by non-linear averaging. In our study, there was evidence that properties of CEOAE non-linear components are related to the post-conception age (PCA) in that the levels and latency of CEOAE frequency components changed until the age of about 38 weeks post-conception, whereas after 38 weeks, CEOAE features were very similar to those of term newborns. In particular, the CEOAE levels increased and latency decreased with age. The observed changes in CEOAE properties seem to reveal a development of cochlear active mechanisms, although contributions from outer and middle ear development cannot be excluded. Also, in agreement with previous physiological and behavioral findings, our results revealed that the development of CEOAE properties was not the same for all the frequencies, being greater for frequencies 4 kHz, and resembled the development of the cochlear partition, which proceeds from base to apex.

Acoustic Stimulation↗

PubMed2000

A wavelet-based method for improving signal-to-noise ratio and contrast in MR images.

Magnetic resonance (MR) images acquired with fast measurement often display poor signal-to-noise ratio (SNR) and contrast. With the advent of high temporal resolution imaging, there is a growing need to remove these noise artifacts. The noise in magnitude MR images is signal-dependent (Rician), whereas most de-noising algorithms assume additive Gaussian (white) noise. However, the Rician distribution only looks Gaussian at high SNR. Some recent work by Nowak employs a wavelet-based method for de-noising the square magnitude images, and explicitly takes into account the Rician nature of the noise distribution. In this article, we apply a wavelet de-noising algorithm directly to the complex image obtained as the Fourier transform of the raw k-space two-channel (real and imaginary) data. By retaining the complex image, we are able to de-noise not only magnitude images but also phase images. A multiscale (complex) wavelet-domain Wiener-type filter is derived. The algorithm preserves edges better when the Haar wavelet rather than smoother wavelets, such as those of Daubechies, are used. The algorithm was tested on a simulated image to which various levels of noise were added, on several EPI image sequences, each of different SNR, and on a pair of low SNR MR micro-images acquired using gradient echo and spin echo sequences. For the simulated data, the original image could be well recovered even for high values of noise (SNR approximately 0 dB), suggesting that the present algorithm may provide better recovery of the contrast than Nowak's method. The mean-square error, bias, and variance are computed for the simulated images. Over a range of amounts of added noise, the present method is shown to give smaller bias than when using a soft threshold, and smaller variance than a hard threshold; in general, it provides a better bias-variance balance than either hard or soft threshold methods. For the EPI (MR) images, contrast improvements of up to 8% (for SNR = 33 dB) were found. In general, the improvement in contrast was greater the lower the original SNR, for example, up to 50% contrast improvement for SNR of about 20 dB in micro-imaging. Applications of the algorithm to the segmentation of medical images, to micro-imaging and angiography (where the correct preservation of phase is important for flow encoding to be possible), as well as to de-noising time series of functional MR images, are discussed.

Algorithms↗

PubMed2004

Mother rotors and the mechanisms of D600-induced type 2 ventricular fibrillation.

BACKGROUND: Two types of ventricular fibrillation (VF) have been demonstrated in isolated rabbit hearts during D600 infusion. Type 1 VF is characterized by the presence of multiple, wandering wavelets, whereas type 2 VF shows local spatiotemporal periodicity. We hypothesized that a single mother rotor underlies type 2 VF. METHODS AND RESULTS: One (protocol I) or 2 (protocol II) cameras were used to map the epicardial ventricular activations in Langendorff-perfused rabbit hearts. Multiple episodes of type 2 VF were induced in 22 hearts by high-concentration (> or =2.5 mg/L) D600 (protocol I). During type 2 VF, a single spiral wave (n=19) and/or an epicardial breakthrough pattern (n=11) was present in 14 hearts. These spiral waves either slowly drifted or intermittently anchored on the papillary muscle (PM) of the left ventricle. Dominant-frequency (DF) analyses showed that the highest local DF was near the PM (12.5+/-1.1 Hz). There was an excellent correlation between the highest local DF of these spiral waves and breakthroughs (11.8+/-1.7 Hz) and the DF of simultaneously obtained global pseudo-ECG (11.2+/-1.8 Hz, r=0.97, P<0.0001) during type 2 VF. We also successfully reproduced the major features of type 2 VF by using the Luo-Rudy action-potential model in a simulated, 3-dimensional tissue slab, under conditions of reduced excitability and flat action-potential duration restitution. CONCLUSIONS: Either a stationary or a slowly drifting mother rotor can result in type 2 VF. Colocalization of the stationary mother rotors with the PM suggests the importance of underlying anatomic structures in mother rotor formation.

Action Potentials↗

PubMed2004

A deformable-model approach to semi-automatic segmentation of CT images demonstrated by application to the spinal canal.

Because of the importance of accurately defining the target in radiation treatment planning, we have developed a deformable-template algorithm for the semi-automatic delineation of normal tissue structures on computed tomography (CT) images. We illustrate the method by applying it to the spinal canal. Segmentation is performed in three steps: (a) partial delineation of the anatomic structure is obtained by wavelet-based edge detection; (b) a deformable-model template is fitted to the edge set by chamfer matching; and (c) the template is relaxed away from its original shape into its final position. Appropriately chosen ranges for the model parameters limit the deformations of the template, accounting for interpatient variability. Our approach differs from those used in other deformable models in that it does not inherently require the modeling of forces. Instead, the spinal canal was modeled using Fourier descriptors derived from four sets of manually drawn contours. Segmentation was carried out, without manual intervention, on five CT data sets and the algorithm's performance was judged subjectively by two radiation oncologists. Two assessments were considered: in the first, segmentation on a random selection of 100 axial CT images was compared with the corresponding contours drawn manually by one of six dosimetrists, also chosen randomly; in the second assessment, the segmentation of each image in the five evaluable CT sets (a total of 557 axial images) was rated as either successful, unsuccessful, or requiring further editing. Contours generated by the algorithm were more likely than manually drawn contours to be considered acceptable by the oncologists. The mean proportions of acceptable contours were 93% (automatic) and 69% (manual). Automatic delineation of the spinal canal was deemed to be successful on 91% of the images, unsuccessful on 2% of the images, and requiring further editing on 7% of the images. Our deformable template algorithm thus gives a robust segmentation of the spinal canal on CT images. The method can be extended to other structures, although it remains to be shown that chamfer matching is sufficiently robust for the delineation of soft-tissue structures surrounded by soft tissue.

Algorithms↗