A new high resolution color flow system using an eigendecomposition-based adaptive filter for clutter rejection

We present a new signal processing strategy for high frequency color flow mapping in moving tissue environments. A new application of an eigendecomposition-based clutter rejection filter is presented with modifications to deal with high blood-to-clutter ratios (BCR). Additionally, a new method for correcting blood velocity estimates with an estimated tissue motion profile is detailed. The performance of the clutter filter and velocity estimation strategies is quantified using a new swept-scan signal model. In vivo color flow images are presented to illustrate the potential of the system for mapping blood flow in the microcirculation with external tissue motion.     

Real-time adaptive clutter rejection filtering in color flow imaging using power method iterations

We propose a new algorithm for real-time, adaptive-clutter-rejection filtering in ultrasound color flow imaging (CFI) and related techniques. The algorithm is based on regression filtering using eigenvectors of the signal correlation matrix as a basis for representing clutter, a method that previously has been considered too computationally demanding for real-time processing in general CFI applications. The data acquisition and processing scheme introduced allows for a more localized sampling of the clutter statistics and, therefore, an improved clutter attenuation for lower filter orders. By using the iterative power method technique, the dominant eigenvalues and corresponding eigenvectors of the correlation matrix can be estimated efficiently, rendering real-time operation feasible on desktop computers. A new adaptive filter order algorithm is proposed that successfully estimates the proper dimension of the clutter basis, previously one of the major drawbacks of this clutter-rejection technique. The filter algorithm performance and computational demands has been compared to that of conventional clutter filters. Examples have been included which confirms that, by adapting the clutter-rejection filter to estimates of the clutter-signal statistics, improved attenuation of the clutter signal can be achieved in normal as well as more excessive cases of tissue movement and acceleration.     

Adaptive clutter rejection for ultrasound color flow imaging based on recursive eigendecomposition

In the conventional eigenfilter used to reject clutter components of ultrasound color flow imaging, input samples are required to be statistically stationary. However, clutter movements may vary over the depth of the imaged area, which makes the eigenfilter less efficient. In the current study, a novel clutter rejection method is proposed based on the recursive eigendecomposition algorithm. In this method, the current eigenvector matrix of the ultrasound echo correlation matrix, which will be used to construct the clutter subspace, is determined by previous eigenvector matrices and the current input. After the estimated clutter signal is obtained by projecting the original input into the clutter space, each filtered output is eventually obtained by subtracting the estimated clutter signal from the original input. This procedure is iterated for each sample volume along the depth. During the updating process, a forgetting factor is introduced to determine proper weights for different inputs. Simulated data in 3 situations and in vivo data collected from human carotid arteries are used to compare the proposed method with other popular clutter filters. Results show that the proposed method can achieve the most accurate velocity profiles in all simulation situations and introduces the fewest velocity artifacts in the tissue region in the in vivo experiment.     

A highly adaptive detector system for high resolution neutron imaging

An optimized detector system that allows high-resolution neutron imaging with desired flexibility is described. The presented system can be adapted and integrated with standard CCD-based neutron detectors. Novel neutron scintillating materials with good photon discrimination and optical lens components are tested and optimized for high-resolution neutron tomographic purposes. The presented detector system provides variable field of view and can be used in combination with different techniques, including dark-field, energy-selective, and neutron spin polarized imaging.     

Edge‐adaptive color interpolation for complementary color filter array

Complementary color filter array (CCFA) is widely used in consumer‐level digital video cameras, since it not only has high sensitivity and good signal‐to‐noise ratio in low‐light condition but also is compatible with the interlaced scanning used in broadcast systems. However, the full‐color images obtained from CCFA suffer from the color artifacts such as false color and zipper effects. These artifacts can be removed with edge‐adaptive color interpolation (ECI) approaches which are generally used in primary color filter array (PCFA). Unfortunately, the unique array pattern of CCFA makes it difficult that CCFA adopts ECI approaches. Therefore, to apply ECI approaches suitable for CCFA to color interpolation is one of the major issues to reconstruct the full‐color images. In this paper, we propose a new ECI algorithm for CCFA. To estimate an edge direction precisely and enhance the quality of the reconstructed image, a function of spatial variances is used as a weight, and new color conversion matrices are presented for considering various edge directions. Experimental results indicate that the proposed algorithm outperforms the conventional method with respect to both objective and subjective criteria. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 92–102, 2006     

Clutter filter design for ultrasound color flow imaging

For ultrasound color flow images with high quality, it is important to suppress the clutter signals originating from stationary and slowly moving tissue sufficiently. Without sufficient clutter rejection, low velocity blood flow cannot be measured, and estimates of higher velocities will have a large bias. The small number of samples available (8 to 16) makes clutter filtering in color flow imaging a challenging problem. In this paper, we review and analyze three classes of filters: finite impulse response (FIR), infinite impulse response (IIR), and regression filters. The quality of the filters was assessed based on the frequency response, as well as on the bias and variance of a mean blood velocity estimator using an autocorrelation technique. For FIR filters, the frequency response was improved by allowing a non-linear phase response. By estimating the mean blood flow velocity from two vectors filtered in the forward and backward direction, respectively, the standard deviation was significantly lower with a minimum phase filter than with a linear phase filter. For IIR filters applied to short signals, the transient part of the output signal is important. We analyzed zero, step, and projection initialization, and found that projection initialization gave the best filters. For regression filters, polynomial basis functions provide effective clutter suppression. The best filters from each of the three classes gave comparable bias and variance of the mean blood velocity estimates. However, polynomial regression filters and projection-initialized IIR filters had a slightly better frequency response than could be obtained with FIR filters     

A new adaptive mean frequency estimator: application to constant variance color flow mapping

A class of adapted mean frequency estimators is proposed for color flow mapping. These estimators can be fitted to the specific characteristics of a given Doppler signal to optimize the compromise between the range of analysable frequencies and the variance of mean frequency estimation. A sub-optimal estimator is derived for real-time applications, and an adaptive criterion based on the Doppler signal variance is developed for color flow mapping applications. Its performance is compared to that of the usual correlation phase estimator on simulated Doppler signals and on synthetic Doppler images. An improvement in image quality is achieved, mainly for low signal-to-noise ratio Doppler signals.     

局部高空间分辨率的应用适应性PET系统设计初探

研制成本可负担的高空间分辨率正电子发射断层成像(positron emission tomography,PET)系统在PET成像应用中具有决定性的意义,也是PET成像面临的关键性挑战之一。设想一种PET系统,能够根据应用的需求对不同性能的探测器进行布局,在一个具体时刻,对部分成像区域获得很高的性能,而在其他的区域获得普通性能。提出了一种应用适应性PET系统原型,由大部分普通固有空间分辨率的探测模块和少量更高甚至极端高固有空间分辨率的探测模块组成。研究了在含有连续放置的一段高固有空间分辨率探测模块的PET系统中,高性能模块的布局位置和数量对视场内不同位置点的空间分辨率的影响。初步研究结果表明,所提出的系统能够为局部区域带来高空间分辨率,其空间分辨率提升程度与高性能模块布局位置有关,在同一高性能模块布局位置下,视场中不同位置点的提升程度不同。该研究结果也显示,根据应用需求规划探测模块的构成和布局以在感兴趣区域获得局部高空间分辨率是可能的。     

High-efficiency micro-optical color filter for liquid-crystal projection system applications

High-efficiency color filters composed of a microprism array, optical interference color filters, and a microlens array light compressor were developed to increase the optical throughput of liquid-crystal projection systems. The new devices utilize the energy of whole spectra by taking full advantage of a light compressor and interference dichroic filters to distribute the energy of spectra to the respective color pixel area. Thus high-efficiency micro-optical color filters allow efficient utilization of the energy of incident light and maximize the optical throughput of the projection system.     

Single-ensemble-based eigen-processing methods for color flow imaging--Part I. The Hankel-SVD filter

Because of their adaptability to the slow-time signal contents, eigen-based filters have shown potential in improving the flow detection performance of color flow images. This paper proposes a new eigen-based filter called the Hankel-SVD filter that is intended to process each slowtime ensemble individually. The new filter is derived using the notion of principal Hankel component analysis, and it achieves clutter suppression by retaining only the principal components whose order is greater than the clutter eigen-space dimension estimated from a frequency based analysis algorithm. To assess its efficacy, the Hankel-SVD filter was first applied to synthetic slow-time data (ensemble size: 10) simulated from two different sets of flow parameters that model: 1) arterial imaging (blood velocity: 0 to 38.5 cm/s, tissue motion: up to 2 mm/s, transmit frequency: 5 MHz, pulse repetition period: 0.4 ms) and 2) deep vessel imaging (blood velocity: 0 to 19.2 cm/s, tissue motion: up to 2 cm/s, transmit frequency: 2 MHz, pulse repetition period: 2.0 ms). In the simulation analysis, the post-filter clutter-to- blood signal ratio (CBR) was computed as a function of blood velocity. Results show that for the same effective stopband size (50 Hz), the Hankel-SVD filter has a narrower transition region in the post-filter CBR curve than that of another type of adaptive filter called the clutter-downmixing filter. The practical efficacy of the proposed filter was tested by application to in vivo color flow data obtained from the human carotid arteries (transmit frequency: 4 MHz, pulse repetition period: 0.333 ms, ensemble size: 10). The resulting power images show that the Hankel-SVD filter can better distinguish between blood and moving-tissue regions (about 9 dB separation in power) than the clutter-downmixing filter and a fixed-rank multi ensemble-based eigen-filter (which showed a 2 to 3 dB separation).     

Underwater single beam circumferentially scanning detection system using range-gated receiver and adaptive filter

Underwater target detection and ranging in seawater are of interest in unmanned underwater vehicles. This study presents an underwater detection system that synchronously scans a collimated laser beam and a narrow field of view to circumferentially detect an underwater target. Hybrid methods of range-gated and variable step-size least mean squares (VSS-LMS) adaptive filter are proposed to suppress water backscattering. The range-gated receiver eliminates the backscattering of near-field water. The VSS-LMS filter extracts the target echo in the remaining backscattering and the constant fraction discriminator timing method is used to improve ranging accuracy. The optimal constant fraction is selected by analysing the jitter noise and slope of the target echo. The prototype of the underwater detection system is constructed and tested in coastal seawater, then the effectiveness of backscattering suppression and high-ranging accuracy is verified through experimental results and analysis discussed in this paper.     

A new chemically amplified resist for high resolution patterning by E-beam lithography

In this work, we have undertaken evaluation of the lithography property of a recently available chemically amplified resist (CAR) resist, UV1116 supplied by Rohm and Haas Company. Systematic study of the EBL property such as sensitivity, contrast, high resolution limit and dense capability, as well as resistance to plasma dry etching has been carried out. In comparison with the performance of UVIII, we conclude that the UV1116 can be a good alternative with better lithography quality.     

A new adaptive analog test and diagnosis system

This paper presents a low-cost analog test system with diagnosis capabilities. The tester is able to detect faults in any linear circuit by learning a reference circuit behavior in a first step, and comparing this behavior against the output of the circuit under test in a second step. For a faulty circuit, a third step takes place to locate the fault. The diagnosis method consists in injecting probable faults in a mathematical model of the circuit, and later comparing its output with the output of the real faulty circuit. This system has been successfully applied to a case study, a biquad filter. Soft, large, and hard deviations on components, as well as faults in operational amplifiers, were considered. Experimental results have proven the feasibility and efficiency of the proposed test and diagnosis system     

基于有限范围自适应卡尔曼滤波的结构损伤识别方法

在土木结构的健康监测中,当破坏发生时能够立即对结构的损伤做出判断和评估是一项非常重要的工作.本文采用了一种基于广义卡尔曼滤波的自适应追踪技术对结构的参数进行辨识.该方法能够追踪结构的时变参数,并对结构损伤的位置、大小以及发生的时间做出判断.数值仿真的结果表明该方法对于线性和非线性结构的参数变化具有敏感性,能够有效地检测出结构的损伤.     

Basic study on heat rejection system using high heat flux micro channel evaporator

Thermal management system which can reject very high amount of heat by small thermal devices will be required for future space systems. Our purpose is to develop miniaturized heat rejection system that can reject more than 100 W/cm². In the evaporator, thin liquid film vaporization which can dissipate very high heat flux, was utilized. The liquid film is stabilized in micro-channels by capillary forces. The microchannels are fabricated by chemical etching on silicon and copper plate. Also miniaturized condenser which utilized droplet condensation was tested. Droplets were produced on a cooled plate covered by non-wetting coating. After we built a heat rejection system constructed by above mentioned evaporator and condenser, influence of heat flux, coolant flow rate, and inlet temperature on the temperature of the heater element were investigated. Water is used as working fluid. Heat flux of 100 W/cm² could be achieved for water inlet temperature in flow rate of 3.0 mL/min. The temperature of the heater element is kept constant at about 120°C.     

Prediction of flow stress in isothermal compression of Ti60 alloy using an adaptive network-based fuzzy inference system

Isothermal compression of Ti60 titanium alloy at the deformation temperatures ranging from 960 to 1110 °C, the strain rates ranging from 0.001 to 10 s⁻¹ and the height reductions of 60% were carried out on a Gleeble–3800 simulator. An adaptive network-based fuzzy inference system (ANFIS) model has been established to predict the flow stress of Ti60 alloy during hot deformation process. A comparative evaluation of the predicted and the experimental results has shown that the ANFIS model used to predict the flow stress of Ti60 titanium alloy has a high accuracy. The maximum difference and the average difference between the predicted and the experimental flow stress are 13.83% and 5.15%, respectively. The comparison between the predicted results based on the ANFIS model for flow stress and those using the regression method has illustrated that the ANFIS model is more efficient in predicting the flow stress of Ti60 alloy.     

Performance analysis of vapor compression refrigeration system using an adaptive neuro-fuzzy inference system

In this work, an experimental investigation is carried out with R134a and LPG refrigerant mixture (composed of R134a and LPG in the ratio of 28:72 by weight) as an alternative to R134a in a vapor compression refrigeration system. Performance tests were performed with different evaporator temperatures under controlled ambient conditions. The results showed that the R134a/LPG mixture has a higher coefficient of performance (COP) than R134a by about 15.28% in the studied range. The applicability of adaptive neuro-fuzzy inference system (ANFIS) to predict the COP of R134a/LPG system was also investigated. An ANFIS model for the system was developed. The comparison of statistical analysis of mathematical and ANFIS model predictions respectively in terms of the absolute fraction of variance (0.982 and 0.994), the root mean square error (0.0056 and 0.0050) and the mean absolute percentage error (0.286% and 0.217%) showed that ANFIS model gave the better statistical prediction efficiency.     

基于自适应卡尔曼滤波方法的结构损伤识别实验研究

通过一系列的实验,分析了自适应卡尔曼滤波方法在结构损伤识别中的有效性和准确性.实验中为了模拟结构在振动过程中的突然损伤,提出了一种模拟在线损伤的刚度元件装置,该装置可以实现结构在振动过程中刚度发生突然变化.通过对实验结构在不同激励下的各种损伤情况进行模拟,并对测量数据进行分析,结果表明,自适应卡尔曼滤波方法能够有效地追踪结构参数的变化.从而识别出结构的损伤,包括损伤的位置、大小和发生时刻,具有较高的实际应用价值.