Wavelet-based enhancement of signal-averaged electrocardiograms for late potential detection

An optimal wavelet filter to improve the signal-to-noise ratio (SNR) of the signal-averaged electrocardiogram is described. As the averaging technique leads to the best unbiased estimator, the challenge is to attenuate the noise while preserving the low amplitude signals that are usually embedded in it. An optimal, in the mean-square sense, wavelet-based filter has been derived from the model of the signal. However, such a filter needs exact knowledge of the noise statistic and the noise-free signal. Hence, to implement such a filter, a method based on successive sub-averaging and wavelet filtering is proposed. Its performance was evaluated using simulated and real ECGs. An improvement in SNR of between 6 and 10 dB can be achieved compared to a classical averaging technique which uses an ensemble of 64 simulated ECG beats. Tests on real ECGs demonstrate the utility of the method as it has been shown that by using fewer beats in the filtered ensemble average, one can achieve the same noise reduction. Clinical use of this technique would reduce the ensemble needed for averaging while obtaining the same diagnostic result.     

Filters and Fourier analysis of gated blood pool studies: a search for the optimal combination

Fourier analysis of gated blood pool studies is performed after filtering the raw data by a spatial median 3 x 3, 9 x 9 or temporo-spatial 9 x 9 x 9 filter. 20 patients and a dynamic cardiac phantom were studied to determine the quantitative effects of these filters and of multiharmonic Fourier filtering (MHFF). The filtered MHFF data, with or without preprocessing, were compared with a 3 D or 2 D filter to the raw data using a chi 2 distribution. The MHFF (two or three harmonics) procedure applied to the raw data of patients without any preprocessing produced the smallest chi 2 value, thus demonstrating the very close relationship between filtered images and raw data. Preprocessing the raw data by the median filter also preserved the signal when two or three harmonics were applied, whereas the 3 D and 2 D (9 x 9) filters did not. The phantom study also demonstrated that MHFF preserved the signal better than any other preprocessing. The median filter introduced a smaller distortion than the 2 D (9 x 9) and 3 D filters. It is concluded that MHFF applied with two or three harmonics on the raw data or after preprocessing by a median (3 x 3) filter is the most successful way of preserving the real signal. It is believed that the other filters should be avoided. The clinical advantage of MHFF processing is to provide both very accurate filtering and parametric images.     

Wavelet-based enhancement of signalaveraged electrocardiograms for late potential detection

An optimal wavelet filter to improve the signal-to-noise ratio (SNR) of the signal-averaged electrocardiogram is described. As the averaging technique leads to the best unbiased estimator, the challenge is to attenuate the noise while preserving the low amplitude signals that are usually embedded in it. An optimal, in the meansquare sense, wavelet-based filter has been derived from the model of the signal. However, such a filter needs exact knowledge of the noise statistic and the noise-free signal. Hence, to implement such a filter, a method based on successive subaveraging and wavelet filtering is proposed. Its performance was evaluated using simulated and real ECGs. An improvement in SNR of between 6 and 10 dB can be achieved compared to a classical averaging technique which uses an ensemble of 64 simulated ECG beats. Tests on real ECGs demonstrate the utility of the method as it has been shown that by using fewer beats in the filtered ensemble average, one can achieve the same noise reduction. Clinical use of this technique would reduce the ensemble needed for averaging while obtaining the same diagnostic result.     

基于低秩理论的超声血流壁滤波器

传统的超声血流壁滤波器采用单一的截止频率,对于心跳、呼吸等因素所产生的不同组织运动滤波效果不佳。提出一种基于低秩理论的超声血流壁滤波方法。通过分析超声血流的特点,将其公式化并建立低秩模型,模型包括一个矩阵秩的最小化和一个稀疏矩阵问题。松弛后转化为最小化核范数与1范数的线性组合,成为凸优化可解问题,从而实现低秩滤波。这种滤波的创新性在于它是自适应的,同时考虑了信号的低秩性与稀疏性两个特点,通过线性组合使得滤波效果达到最优。通过低秩滤波,超声血流仿真数据得到更加精确的血流信号。对比传统的FIR滤波,分别采用12阶、56阶和92阶的FIR滤波器,得到血流信号对比实际仿真数据的RMS误差分别约为34%、16%和12%,而低秩滤波的RMS误差则低于0.001%。低秩滤波相比传统FIR滤波,不仅提高了精度,而且滤波后的信号长度不会损失。但是低秩模型计算过于复杂,因此目前还很难应用在实时的超声系统中。     

Evoked potential estimation using modified time-sequenced adaptive filter

A method called modified time-sequenced adaptive filtering (MTSAF) is applied to estimate evoked potential (EP) signals and track the temporal variations of EPs. The MTSAF consists of a set of adaptive filters (AFs), with each processing a time segment of EP data. After convergence, each AF reaches the best estimation of EP signals over its own time segment in terms of minimum mean squared error (MMSE). Numerical results of simulated and human EP data show that the MTSAF reaches better estimation of EPs than a conventional adaptive signal enhancer (ASE). With the MTSAF, the temporal variations of EPS across trials can be estimated to reveal more subtle variations of EPs, which may be of clinical value.     

A Wiener filter for nuclear medicine images

To improve the quality of digital nuclear medicine images, we have developed a new implementation of the Wiener restoration filter. The Wiener filter uses as its optimality criterion the minimization of the mean-square error between the undistorted image of the object and the filtered image. In order to form this filter, the object and noise power spectrums are needed. The noise power spectrum for the count-dependent Poisson noise of nuclear medicine images is shown to have a constant average magnitude equal to the total count in the image. The object power spectrum is taken to be the image power spectrum minus the total count, except in the noise dominated region of the image power spectrum where a least-squares-fitted exponential is used. Processing time is kept to a clinically acceptable time frame through use of an array processor. Pronounced noise suppression and detail enhancement are noted with use of this filter with clinical images.     

Quantitative gated SPECT: the effect of reconstruction filter on calculated left ventricular ejection fractions and volumes

Gated SPECT (GSPECT) offers the possibility of obtaining additional functional information from perfusion studies, including calculation of left ventricular ejection fraction (LVEF). The calculation of LVEF relies upon the identification of the endocardial surface, which will be affected by the spatial resolution and statistical noise in the reconstructed images. The aim of this study was to compare LVEFs and ventricular volumes calculated from GSPECT using six reconstruction filters. GSPECT and radionuclide ventriculography (RNVG) were performed on 40 patients; filtered back projection was used to reconstruct the datasets with each filter. LVEFs and volumes were calculated using the Cedars-Sinai QGS package. The correlation coefficient between RNVG and GSPECT ranged from 0.81 to 0.86 with higher correlations for smoother filters. The narrowest prediction interval was 111 +/- 2%. There was a trend towards higher LVEF values with smoother filters, the ramp filter yielding LVEFs 2.55 +/- 3.10% (p < 0.001) lower than the Hann filter. There was an overall fall in ventricular volumes with smoother filters with a mean difference of 13.98 +/- 10.15 ml (p < 0.001) in EDV between the Butterworth-0.5 and Butterworth-0.3 filters. In conclusion, smoother reconstruction filters lead to lower volumes and higher ejection fractions with the QGS algorithm, with the Butterworth-0.4 filter giving the highest correlation with LVEFs from RNVG. Even if the optimal filter is chosen the uncertainty in the measured ejection fractions is still too great to be clinically acceptable.     

Oversampled filters for quantitative volumetric PET reconstruction

Three-dimensional filtered backprojection uses filters generally specified in the Fourier domain. Implementing these filters by direct sampling in the Fourier domain produces an artifact in the reconstructed images consisting primarily of a DC shift. This artifact is caused by aliasing of the reconstruction filter. We have developed a filter construction technique using Fourier domain oversampling, which reduces the artifact. A method to construct the filter efficiently without the need to create and store the entire oversampled filter array is also presented. Quantitative accuracy in filtered backprojection is of particular importance in multiple-pass algorithms used to reconstruct data from cylindrical PET scanners. We are able to implement such algorithms without fitting the reprojected views to the scanner data.     

Design and evaluation of an external filter technique for exposure equalization in mammography.

We are developing an external filter method for equalizing x-ray exposure in the peripheral region of the breast. This method requires the use of only a limited number of custom-built filters for different breast shapes in a given view. This paper describes the design methodology for these external filters. The filter effectiveness was evaluated through a simulation study on 171 mediolateral and 196 craniocaudal view digitized mammograms and through imaging of a breast phantom. The degree of match between the simulated filter and the individual 3-D exposure profiles at the breast periphery was quantified. An analysis was performed to investigate the effect of filter misalignment. The simulation study indicates that the filter is effective in equalizing exposures for more than 80% of the breast images in our database. The tolerance in filter misalignment was estimated to be about +/- 2 mm for the CC view and +/- 1 mm for the MLO view at the image plane. Some misalignment artifacts were demonstrated with simulated filtered mammograms.     

Phantom experiments to improve parathyroid lesion detection

This investigation tested the hypothesis that visual analysis of iteratively reconstructed tomograms by ordered subset expectation maximization (OSEM) provides the highest accuracy for localizing parathyroid lesions using 99mTc-sestamibi SPECT data. From an Institutional Review Board approved retrospective review of 531 patients evaluated for parathyroid localization, image characteristics were determined for 85 99mTc-sestamibi SPECT studies originally read as equivocal (EQ). Seventy-two plexiglas phantoms using cylindrical simulated lesions were acquired for a clinically realistic range of counts (mean simulated lesion counts of 75 +/- 50 counts/pixel) and target-to-background (T:B) ratios (range = 2.0 to 8.0) to determine an optimal filter for OSEM. Two experienced nuclear physicians graded simulated lesions, blinded to whether chambers contained radioactivity or plain water, and two observers used the same scale to read all phantom and clinical SPECT studies, blinded to pathology findings and clinical information. For phantom data and all clinical data, T : B analyses were not statistically different for OSEM versus FB, but visual readings were significantly more accurate than T : B (88 +/- 6% versus 68 +/- 6%, p = 0.001) for OSEM processing, and OSEM was significantly more accurate than FB for visual readings (88 +/- 6% versus 58 +/- 6%, p < 0.0001). These data suggest that visual analysis of iteratively reconstructed MIBI tomograms should be incorporated into imaging protocols performed to localize parathyroid lesions.     

Selection of biorthogonal filters for image compression of MR images using wavelet packets

We present an analysis of different filter banks for the compression of magnetic resonance (MR) images of the human brain using wavelet packets based on biorthogonal filters. Initially, peak signal to noise ratio (PSNR) and normalized root mean square (RMS) error criteria are calculated for a series of images compressed with a 33:1 ratio, using filter banks based on biorthogonal wavelet packets. The results lead us to choose a few of these filter banks as optimal for image compression. One of these filters is employed to compress several images at four different compression ratios: 12.5:1, 25:1, 37.5:1 and 50:1. The quality of these images was evaluated by visual analysis by a group of seven experts who graded image quality on a 0-7 scale. Results show that using these filters, we can compress images to a rate of around 30:1 without introducing noticeable differences. Other applications for these filters are currently under study and include the compression/fusion of MR image stacks in order to obtain even better reductions in the amount of data needed to reconstruct complete MRI studies.     

Filter calculation for x-ray tomosynthesis reconstruction

Filtered backprojection reconstruction is an efficient image reconstruction method which is widely used in CT and 3D x-ray imaging. The way data have to be filtered depends on the acquisition geometry and the number of projections (views) which were acquired. For standard geometries like circle or helix it is known how to effectively filter the data. But there are acquisition geometries for which the application of standard filters yields poor results, e.g. in situations where the number of views is very small or for a limited angular range. In tomosynthesis, both conditions apply, i.e. the number of projections is typically very small and, moreover, the angular coverage is much less than 180°. This paper proposes a new method to design effective filters which are specific for the acquisition geometry. Examples from x-ray tomosynthesis are utilized to demonstrate the excellent performance of the proposed method.     

TIPS bilateral noise reduction in 4D CT perfusion scans produces high-quality cerebral blood flow maps

Cerebral computed tomography perfusion (CTP) scans are acquired to detect areas of abnormal perfusion in patients with cerebrovascular diseases. These 4D CTP scans consist of multiple sequential 3D CT scans over time. Therefore, to reduce radiation exposure to the patient, the amount of x-ray radiation that can be used per sequential scan is limited, which results in a high level of noise. To detect areas of abnormal perfusion, perfusion parameters are derived from the CTP data, such as the cerebral blood flow (CBF). Algorithms to determine perfusion parameters, especially singular value decomposition, are very sensitive to noise. Therefore, noise reduction is an important preprocessing step for CTP analysis. In this paper, we propose a time-intensity profile similarity (TIPS) bilateral filter to reduce noise in 4D CTP scans, while preserving the time-intensity profiles (fourth dimension) that are essential for determining the perfusion parameters. The proposed TIPS bilateral filter is compared to standard Gaussian filtering, and 4D and 3D (applied separately to each sequential scan) bilateral filtering on both phantom and patient data. Results on the phantom data show that the TIPS bilateral filter is best able to approach the ground truth (noise-free phantom), compared to the other filtering methods (lowest root mean square error). An observer study is performed using CBF maps derived from fifteen CTP scans of acute stroke patients filtered with standard Gaussian, 3D, 4D and TIPS bilateral filtering. These CBF maps were blindly presented to two observers that indicated which map they preferred for (1) gray/white matter differentiation, (2) detectability of infarcted area and (3) overall image quality. Based on these results, the TIPS bilateral filter ranked best and its CBF maps were scored to have the best overall image quality in 100% of the cases by both observers. Furthermore, quantitative CBF and cerebral blood volume values in both the phantom and the patient data showed that the TIPS bilateral filter resulted in realistic mean values with a smaller standard deviation than the other evaluated filters and higher contrast-to-noise ratios. Therefore, applying the proposed TIPS bilateral filtering method to 4D CTP data produces higher quality CBF maps than applying the standard Gaussian, 3D bilateral or 4D bilateral filter. Furthermore, the TIPS bilateral filter is computationally faster than both the 3D and 4D bilateral filters.     

Optimizing the solid-phase immunofiltration assay. A rapid alternative to immunoassays

The technical variables of the solid-phase immunofiltration assay (SPIA) for the detection of antibodies bound to antigens on a solid-phase filter have been investigated. The binding to solid-phase filters of 125I-labelled axial filament proteins derived from Treponema phagedenis and the optimal conditions for blocking non-specific protein binding were analysed. Axial filament was applied to nitrocellulose, Hybond Nylon and Zeta Probe. After extensive rinsing, the highest amount (68%) of axial filament was observed bound to Zeta Probe. However, blocking non-specific protein binding by pre-wetting the filter with rinsing buffer containing 0.5% Tween 20, prevented the binding of protein to the filter only when nitrocellulose was used as solid phase. Tween 20 (0.5%) in the rinsing and incubation solutions was found to be necessary for the reduction of non-specific binding of contaminants in turbid sera. However, the use of such solutions resulted in a substantial leakage of antigen (47%) during rinsing procedures. Binding of antigen-specific antibody was analysed using 125I-labelled protein A. The maximal possible binding of the antibody occurred within 5 min when the antibody solution was filtered. For optimal binding of 125I-labelled protein A an incubation time of 1 h was needed. It is suggested that solid-phase immunofiltration may provide a rapid alternative for radioimmunoassays or enzyme immunoassays for the detection of specific antibodies.     

Signal to noise ratio based filter optimization in triple energy window scatter correction

Triple energy window (TEW) scatter correction estimates the contribution of scattered photons to the acquisition data by acquiring additional data through two narrow energy windows placed adjoined to the main (photopeak) energy window. The contribution is estimated by linear interpolation and then subtracted. Noise amplification is reduced by filtering both the photopeak scintigram and the scatter estimate. We have studied the filter settings of each filter using a physical phantom filled with a 201Tl-solution resulting in count densities comparable to clinical studies. The performance of order-8 Butterworth filters at different cut-off frequencies (CoFs) were compared based on signal to noise ratios (SNRs). The highest SNRs were obtained when the noisy scatter information was strongly filtered with the CoF less than or equal to 0.07 cycles/pixel (cpp). The best CoF for the filter of the photopeak image is object size dependent; smaller objects require a higher CoF. For objects with a size near the SPECT spatial resolution (approximately 15 mm) the optimal CoF is equal to 0.18 cpp. For larger objects (31.8 mm) the highest SNR was obtained with a CoF equal to 0.13 cpp. A CoF equal to 0.16 cpp is a good compromise for all objects with a diameter equal to the spatial resolution or larger. These results depend on the initial signal to noise ratio of the acquisition data and so on the count density.     

Microbiological contamination of drinking water in a commercial household water filter system

The microbiological quality of filtered water in a commercial water filter system (Brita) was tested in households and in two laboratories. In 24 of 34 filters used in households, bacterial counts increased in the filtered water up to 6,000 cfu/ml. In 4 of 6 filters tested in the laboratory, bacterial counts in the fresh filtrate were higher than in tap water after approximately one week of use both at room temperature and at 4°C, suggesting growth or biofilm formation in the filter material. In some cases colony counts in the filtered water were 10,000 times those in tap water. The filter material of 5 of 13 new commercial filters was contaminated with bacteria or moulds. National or international regulatory agencies should ensure that water filters marketed for domestic use do not allow deterioration in the microbiological quality of drinking water.     

Optimal digital filters for long-latency components of the event-related brain potential

A fundamentally important problem for cognitive psychophysiologists is selection of the appropriate off-line digital filter to extract signal from noise in the event-related brain potential (ERP) recorded at the scalp. Investigators in the field typically use a type of finite impulse response (FIR) filter known as moving average or boxcar filter to achieve this end. However, this type of filter can produce significant amplitude diminution and distortion of the shape of the ERP waveform. Thus, there is a need to identify more appropriate filters. In this paper, we compare the performance of another type of FIR filter that, unlike the boxcar filler, is designed with an optimizing algorithm that reduces signal distortion and maximizes signal extraction (referred to here as an optimal FIR filter). We applied several different filters of both types to ERP data containing the P300 component. This comparison revealed that boxcar filters reduced the contribution of high-frequency noise to the ERP but in so doing produced a substantial attenuation of P300 amplitude and, in some cases, substantial distortions of the shape of the waveform, resulting in significant errors in latency estimation. In contrast, the optimal FIR filters preserved P300 amplitude, morphology, and latency and also eliminated high-frequency noise more effectively than did the boxcar filters. The implications of these results for data acquisition and analysis are discussed.     

Glomerular disease search filters for Pubmed, Ovid Medline, and Embase: a development and validation study

ABSTRACT: BACKGROUND: Tools to enhance physician searches of Medline and other bibliographic databases have potential to improve the application of new knowledge in patient care. This is particularly true for articles about glomerular disease, which are published across multiple disciplines and are often difficult to track down. Our objective was to develop and test search filters for PubMed, Ovid Medline, and Embase that allow physicians to search within a subset of the database to retrieve articles relevant to glomerular disease. METHODS: We used a diagnostic test assessment framework with development and validation phases. We read a total of 22,992 full text articles for relevance and assigned them to the development or validation set to define the reference standard. We then used combinations of search terms to develop 997,298 unique glomerular disease filters. Outcome measures for each filter included sensitivity, specificity, precision, and accuracy. We selected optimal sensitive and specific search filters for each database and applied them to the validation set to test performance. RESULTS: High performance filters achieved at least 93.8% sensitivity and specificity in the development set. Filters optimized for sensitivity reached at least 96.7% sensitivity and filters optimized for specificity reached at least 98.4% specificity. Performance of these filters was consistent in the validation set and similar among all three databases. CONCLUSIONS: PubMed, Ovid Medline, and Embase can be filtered for articles relevant to glomerular disease in a reliable manner. These filters can now be used to facilitate physician searching.     

A method for obtaining an approximate Wiener filter

The Wiener restoration filter yields the minimum mean-square error between the restored image and the true object function. However, it has found limited use because, in its usual formulation, it requires information about the object power spectrum which is generally unknown. In this paper, it is shown that the Wiener filter can be derived from the noise-free image power spectrum, and a method is presented for estimating this from the observed data. From this estimate an approximate Wiener filter was calculated. The method was tested on three sets of simulated data which included a constant background, rectangular defects, and Gaussian defects at varying contrast and noise levels. The performance of the approximate Wiener filter was compared both to the true Wiener filter and to the standard 1-2-1 three-point smooth. The results confirmed that the approximate Wiener filter adapted to the information content of the observed data and closely matched the performance of the true Wiener filter. The approximate Wiener filter outperformed the three-point smooth in all cases, especially at low contrast and high noise levels. The approximate Wiener filter can be calculated without operator intervention and requires little additional computation time over conventional Wiener filter techniques.     

Compared study of micro-aggregates filters (output, filtration pressure and study of the deposit with scanning electron microscopy) (author's transl)]

Special filters for the elimination of cellular aggregates were conceived especially to prevent pulmonary complications in patients shocked particularly after massive transfusions as well as to prevent cerebral complications after extra-corporeal circulation. The performances and the conditions of use of these filters (perfusion output, change of the filter) were considered. Four filters were carefully studied: the Fenwal filter, the Swank filter, the Biotest filter and the intersep Johnson and Johnson filter. The following studies were carried out for each filter: the perfusion output (of three bottles filtered one after another with or without pressure); the filtration pressure (Swank technique) of the whole blood up-and-down filter; the viscosity and various hematologic parameters (NF, hemoglobin and gobular ATP); finally, the deposit was studied morphologically with scanning electron microscopy. It appeared that a good capacity of aggregates elimination (decrease of the filtration pressure of 95%) was often linked to a feeble output and the necessity of replacing the filter. The efficacy of the Fenwal filter, the Swank filter, the Biotest filter and the intersept filter was practically the same, but the Intersept filter provided the best output with an equal filtration capacity. The other parameters remained about the same. The deposits included fibrinogen, deformed red blood corpuscules (echinocytes), leucocytes and platelets.