Wavelet-based statistical approach for speckle reduction in medical ultrasound images

A novel speckle-reduction method is introduced, based on soft thresholding of the wavelet coefficients of a logarithmically transformed medical ultrasound image. The method is based on the generalised Gaussian distributed (GGD) modelling of sub-band coefficients. The method used was a variant of the recently published BayesShrink method by Chang and Vetterli, derived in the Bayesian framework for denoising natural images. It was scale adaptive, because the parameters required for estimating the threshold depend on scale and sub-band data. The threshold was computed by Kσ/σ_x, where σ and σ_x were the standard deviation of the noise and the sub-band data of the noise-free image, respectively, and K was a scale parameter. Experimental results showed that the proposed method outperformed the median filter and the homomorphic Wiener filter by 29% in terms of the coefficient of correlation and 4% in terms of the edge preservation parameter. The numerical values of these quantitative parameters indicated the good feature preservation performance of the algorithm, as desired for better diagnosis in medical image processing.     

眼科高频超声成像中斑点噪声抑制算法的研究

目的 斑点噪声是超声图像中存在的固有问题,而在眼科高频超声这种更为精细的超声检查中,有效地抑制斑点噪声能提高图像的质量,有助于临床医生对病情的判别.方法 提出了一种新的基于拉普拉斯（Laplacian）金字塔的多尺度斑点去噪方法.采用Laplacian金字塔,从斑点噪声中分离出临床图像特征,根据每层子带图像不同尺度及特点,从小尺度到大尺度,首先采用改进后的八方向各向异性斑点去噪（SRAD）去除图像斑点,然后增强图像的边缘、细节及对比度等方面.该方法与传统的SRAD滤波及相干增强滤波（CEDIF）进行对比,采用等效视数及算法的时间耗费对实验结果进行量化评估.结果 与传统SRAD滤波及CEDIF滤波方法相比,基于Laplacian金字塔的多尺度各向异性斑点去噪方法均高于前两种方法（1.172 3 vs 1.122 3、0.929 3及0.864 0 vs 1.396 0、1.468 3）.结论 本研究提出的基于Laplacian金字塔的多尺度各向异性斑点去噪方法在更有效地去除图像斑点噪声的同时,能很好地保存图像边缘及图像细节等.     

Frequency domain multiplexing for speckle reduction in optical coherence tomography

Quantitative analysis of optical coherence tomography data can be strongly hampered by speckle. Here, we introduce a new method to reduce speckle, which leverages from Fourier-domain configurations and operates on individual axial scans. By subdividing the digitized spectrum into a number of distinct narrower windows, each with a different center frequency, several independent speckle patterns result. These can be averaged to yield a lower-resolution image with strongly reduced speckle. The full resolution image remains available for human interpretation; the low resolution version can be used for parametric imaging or quantitative analysis. We demonstrate this technique using intravascular optical frequency domain imaging data acquired in vivo.     

Robust non-homomorphic approach for speckle reduction in medical ultrasound images

Most existing wavelet-based image denoising techniques are developed for additive white Gaussian noise. In applications to speckle reduction in medical ultrasound (US) images, the traditional approach is first to perform the logarithmic transform (homomorphic processing) to convert the multiplicative speckle noise model to an additive one, and then the wavelet filtering is performed on the log-transformed image, followed by an exponential operation. However, this non-linear operation leads to biased estimation of the signal and increases the computational complexity of the filtering method. To overcome these drawbacks, an efficient, non-homomorphic technique for speckle reduction in medical US images is proposed. The method relies on the true characterisation of the marginal statistics of the signal and speckle wavelet coefficients. The speckle component was modelled using the generalised Nakagami distribution, which is versatile enough to model the speckle statistics under various scattering conditions of interest in medical US images. By combining this speckle model with the generalised Gaussian signal first, the Bayesian shrinkage functions were derived using the maximum a posteriori (MAP) criterion. The resulting Bayesian processor used the local image statistics to achieve soft-adaptation from homogeneous to highly heterogeneous areas. Finally, the results showed that the proposed method, named GNDShrink, yielded a signal-to-noise ratio (SNR) gain of 0.42 dB over the best state-of-the-art despeckling method reported in the literature, 1.73 dB over the Lee filter and 1.31 dB over the Kaun filter at an input SNR of 12.0 dB, when tested on a US image. Further, the visual comparison of despeckled US images indicated that the new method suppressed the speckle noise well, while preserving the texture and organ surfaces.     

Noise reduction methods for hybrid subtraction

In digital subtraction angiography, hybrid subtraction provides selective vessel images free of soft-tissue motion artifacts but with a lower signal-to-noise ratio (SNR) than temporal subtraction images. An image processing method called measurement-dependent filtering has been developed to enhance the SNR of hybrid images without losing resolution or selectivity. Linear combinations of four images consisting of a pre- and postcontrast dual-energy measurement pair form both the hybrid image and a lower noise but less selective vessel image. The noise-reduced image is derived by combining the low-frequency components of the hybrid image with the high-frequency components of the lower noise image in a variety of ways. The results of the filtering method, when tested on both phantom and clinical data, display images with about the same degree of conspicuity as the hybrid image and a SNR approaching that of the temporal image.     

Optical coherence tomography speckle reduction by a partially spatially coherent source

Speckle in optical coherence tomography (OCT) images originates in the high spatial coherence of incident light that enables interference of light backscattered from spatially heterogenous tissue specimens. We report results of a numerical simulation and an experiment to test speckle reduction using a partially spatially coherent source. A Gaussian-Schell model for a partially spatially coherent source is used in the OCT simulation. For the experiment, such a source was generated by a spatially coherent boardband light source and a multimode fiber. The advantage of using a multimode fiber in combination with a broadband source is the large number of photons per coherence volume. To illustrate speckle reduction with a partially spatially coherent source, we record low-coherence interferograms of a scattering surface using single-mode and multimode source fibers. Interferograms recorded using a single-mode source fiber are indicative of those observed using conventional OCT. Speckle in OCT images recorded using a multimode source fiber is substantially reduced.     

Angular high-speed massively parallel detection spectral-domain optical coherence tomography for speckle reduction

We demonstrate speckle reduction based on angular compounding using parallel-detection spectral-domain optical coherence tomography (OCT). An ultrahigh-speed two-dimensional complementary metal-oxide semiconductor camera acquired angular and spectral interference fringes (128 × 1024 pixels) simultaneously at 15,000 frames/s for a single lateral point. A signal-to-noise ratio improvement of 8 dB was achieved for imaging human skin in vivo by averaging 121 angle-resolved OCT images.     

Cascaded systems analysis of noise reduction algorithms in dual-energy imaging

An important aspect of dual-energy (DE) x-ray image decomposition is the incorporation of noise reduction techniques to mitigate the amplification of quantum noise. This article extends cascaded systems analysis of imaging performance to DE imaging systems incorporating linear noise reduction algorithms. A general analytical formulation of linear DE decomposition is derived, with weighted log subtraction and several previously reported noise reduction algorithms emerging as special cases. The DE image noise-power spectrum (NPS) and modulation transfer function (MTF) demonstrate that noise reduction algorithms impart significant, nontrivial effects on the spatial-frequency-dependent transfer characteristics which do not cancel out of the noise-equivalent quanta (NEQ). Theoretical predictions were validated in comparison to the measured NPS and MTF. The resulting NEQ was integrated with spatial-frequency-dependent task functions to yield the detectability index, d', for evaluation of DE imaging performance using different decomposition algorithms. For a 3 mm lung nodule detection task, the detectability index varied from d' < 1 (i.e., nodule barely visible) in the absence of noise reduction to d' > 2.5 (i.e., nodule clearly visible) for "anti-correlated noise reduction" (ACNR) or "simple-smoothing of the high-energy image" (SSH) algorithms applied to soft-tissue or bone-only decompositions, respectively. Optimal dose allocation (A*, the fraction of total dose delivered in the low-energy projection) was also found to depend on the choice of noise reduction technique. At fixed total dose, multi-function optimization suggested a significant increase in optimal dose allocation from A* = 0.32 for conventional log subtraction to A* = 0.79 for ACNR and SSH in soft-tissue and bone-only decompositions, respectively. Cascaded systems analysis extended to the general formulation of DE image decomposition provided an objective means of investigating DE imaging performance across a broad range of acquisition and decomposition algorithms in a manner that accounts for the spatial-frequency-dependent imaging task.     

MP-PCNN超声多普勒血流信号声谱图降噪去斑方法

为有效抑制超声多普勒血流信号声谱图中的背景噪声和多普勒斑点,提出了Matching Pursuit(MP)及单向衰减阈值脉冲耦合神经网络(MP-PCNN)模型。首先将分段的多普勒超声信号进行MP循环分解,分离噪声与信号,然后用单向衰减阈值PCNN模型计算声谱图在各个灰度等级上的点火时刻图并定位斑点,用中值滤波器抑制斑点。通过对各种信噪比的仿真超声多普勒血流信号处理,实验结果表明,MP-PCNN方法可有效地滤除声谱图中的噪声与斑点,并较好地保持边缘与细节信息,在主观及客观性能比较上优于同类降噪去斑方法。     

Assessment and disease comparisons of hybrid developmental defects

Rodents of the genus Peromyscus are among the most common North American mammals. Crosses between natural populations of two of these species, P. maniculatus (BW) and P. polionotus (PO), produce parent-of-origin effects on growth and development. BW females mated to PO males produce growth-retarded offspring. In contrast, PO females mated to BW males produce overgrown but dysmorphic conceptuses. Variation in imprinted loci and control of genomic imprinting appear to underlie the hybrid effects. Prior morphological and genetic analyses have focused on placental and post-natal growth. Here, we assess the frequency and scope of embryonic defects. The most frequent outcome of the PO x BW cross is death prior to embryonic day 13. Conceptuses lacking an embryo proper are also observed as in gestational trophoblast disease. Among the common embryonic phenotypes described and tabulated are edema, blood vessel enlargement/hemorrhaging, macroglossia, retention of nucleated erythrocytes, placentomegaly. We investigate expression of loci known to be mis-regulated in human growth/placental disorders and/or mouse knockouts with similar phenotypes. These loci are Igf2, Cdkn1c, Grb10, Gpc3, Phlda2 and Rb1. All exhibited significant differences in either placental or embryonic expression levels at one or more of the three timepoints examined. The data underscore the importance of placental gene expression on embryonic defects. We suggest that the hybrid defects offer a novel system to understand how natural allelic combinations interact to produce disease phenotypes. We propose that such interactions and their resulting epimutations may similarly underlie the phenotypic and causal heterogeneity seen in many human diseases.     

Assessment of ocular blood flow in continuous-flow ventricular assist device by laser speckle flowgraphy

Journal of Artificial Organs - Although the influence of continuous-flow left ventricular assist device (CF-LVAD) support on peripheral circulation has been widely discussed, its monitoring...     

Polymorphonuclear leukocytes stimulation by immune complexes. Assessment by nitroblue tetrazolium dye reduction

Insoluble immune complexes and immune aggregates were found to stimulate the activity of the hexose monophosphate shunt as measured by nitroblue tetrazolium reduction in human polymorphonuclear leukocytes. This phenomenon depends more on the size of the complex than on its ability to activate complement.     

Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering

Image quality is important when evaluating ultrasound images of the carotid for the assessment of the degree of atherosclerotic disease, or when transferring images through a telemedicine channel, and/or in other image processing tasks. The objective of this study was to investigate the usefulness of image quality evaluation based on image quality metrics and visual perception, in ultrasound imaging of the carotid artery after normalization and speckle reduction filtering. Image quality was evaluated based on statistical and texture features, image quality evaluation metrics, and visual perception evaluation made by two experts. These were computed on 80 longitudinal ultrasound images of the carotid bifurcation recorded from two different ultrasound scanners, the HDI ATL-3000 and the HDI ATL-5000 scanner, before (NF) and after (DS) speckle reduction filtering, after normalization (N), and after normalization and speckle reduction filtering (NDS). The results of this study showed that: (1) the normalized speckle reduction, NDS, images were rated visually better on both scanners; (2) the NDS images showed better statistical and texture analysis results on both scanners; (3) better image quality evaluation results were obtained between the original (NF) and normalized (N) images, i.e. NF–N, for both scanners, followed by the NF–DS images for the ATL HDI-5000 scanner and the NF–DS on the HDI ATL-3000 scanner; (4) the ATL HDI-5000 scanner images have considerable higher entropy than the ATL HDI-3000 scanner and thus more information content. However, based on the visual evaluation by the two experts, both scanners were rated similarly. The above findings are also in agreement with the visual perception evaluation, carried out by the two vascular experts. The results of this study showed that ultrasound image normalization and speckle reduction filtering are important preprocessing steps favoring image quality, and should be further investigated.     

Multi-label classification of chronically ill patients with bag of words and supervised dimensionality reduction algorithms

ObjectiveThis research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series.MethodsWe combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision.ResultsNon-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches.ConclusionsThe evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification tasks. The study also highlights that dimensionality reduction algorithms based on kernel methods, locality preserving projections or both are good candidates to deal with multi-label classification tasks in medical time series with many missing values and high label density.     

Efficient computation of lod scores: genotype elimination, genotype redefinition, and hybrid maximum likelihood algorithms

Calculation of multilocus lod scores presents challenging problems in numerical analysis, combinatories, programming, and genetics. It is possible to accelerate these computations by exploiting the simple pedigree structure of a CEPH-type pedigree consisting of a nuclear family plus all four grandparents. Lathrop et al. (1986) have done' this by introducing likelihood factorization and transformation rules and Lander & Green (1987) by the method of 'hidden Markov chains'. The present paper explores an alternative approach based on genotype redefinition in the grandparents and systematic phase elimination in all pedigree members. All three approaches accelerate the computation of a single likelihood. Equally relevant to multilocus mapping are search strategies for finding the maximum likelihood estimates of recombination fractions. Hybrid algorithms that start with the EM algorithm and switch midway to quasi-Newton algorithms show promise. These issues are investigated in the context of a simulated 10 locus example. This same example allows us to illustrate a simple strategy for determining locus order.     

Assessment of five rapid tests and two algorithms for the HIV infection diagnosis in Niger

Niger is a Sahelian country of 1,267,000 km2 and 11 M inhabitants (84% living in rural area). The national seroprevalence of the HIV infection is low (2.08% in urban area and 0. 64% in rural area). Because of limited resources, laboratories and qualified personnel are scarce, so the classical strategy using ELISA methods to diagnose HIV is available only in the capital Niamey. In order to define a strategy suitable to the Nigerian field conditions, we have determined the diagnostic value of five commercialised rapid assays (Génie II, InoCheck, Determine, Capillus and Doublecheck). A panel of plasma, whole blood and dried blood spot from 42 positive and 160 negative control individuals was tested and the sensitivity and specificity of each assay were calculated. The two best algorithms using two tests were selected: a algorithm discriminating HIV1 & 2 combining Determine and Genie II showing an excellent sensitivity and specificity (100%) but with many practical constraints; and a non discriminative algorithm combining Determine and Double-check less specific but workable on capillary blood and fully compatible with the field conditions. Its negative predictive value was 100% and its positive predictive value was > 97% for urban population and > 91% for rural population. Dried blood spots on filter paper proved to be very practical and efficient to use by the reference laboratory for the quality control of the peripheral diagnostic centres.     

Rebinning-based algorithms for helical cone-beam CT.

Several image reconstruction algorithms based on rebinning have been proposed recently for helical cone-beam CT. These algorithms separate the 3D reconstruction into a set of independent 2D reconstructions for a set of surfaces: planar or non-planar surfaces are defined and then reconstructed using 2D filtered backprojection from a 2D fan-beam or parallel-beam set of data estimated from the cone-beam (CB) measurements. The first part of this paper presents a unified derivation of rebinning algorithms for planar and non-planar surfaces. An integral equation is derived for the surface allowing the best rebinning and an iterative algorithm converging to the solution of that equation is given. The second part presents an efficient method to correct the residual reconstruction artefacts observed with rebinning algorithms when the cone-angle is too large for the required accuracy. This correction algorithm involves a CB backprojection and the reconstruction time is slightly longer than for the zero-boundary (ZB) method.     

Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed.     

Assessment of competence.

While it is essential that professional competence should be maintained, it is equally important that entry to the specialist ranks should be conditional on the demonstration of an acceptable level of competence. Multiple-choice papers and videotaped consultations are two parts of a multi-format approach to assessment which also includes a trainer's report and an audit report. The number of doctors identified as unsatisfactory at the recertification stage could be reduced by these methods, and the system could also provide a template for the introduction of recertification procedures.