硬化伪影的新型表现形式及其校正

X射线硬化是导致工业CT重建图像质量下降的物理原因之一。硬化伪影通常表现为两种形式,即杯状伪影和带状伪影。描述并证实了硬化伪影的一种新型表现形式,这种伪影与真实结构相关,且分布规则,容易造成伪影与真实结构的混淆。采用线性化校正方法对该伪影进行抑制,提高了重建图像质量,改善了通过CT重建图像进行几何测量的精度。     

低能X射线工业CT图像杯状伪影校正

为了去除X射线工业CT图像中的杯状伪影,提高CT图像的识别能力和量化分析精度,提出一种基于分度投影和权函数的射束硬化校正方法。首先分析得出杯状伪影主要是由X射线连续谱穿过被测物体过程中出现的射束硬化所导致。然后扫描阶梯模型,采集不同厚度下的投影数据并求出线衰减系数,通过拟合曲线,得到硬化模型函数和权函数校正模型函数,并确定权函数。接着,扫描被测圆柱形工件,采集不同分度下的投影数据。最后,针对每一个分度投影数据,采用权函数与当前分度投影数据乘积的方法进行硬化校正。对含有杯状伪影的实际CT图像进行了校正实验,结果表明,与多项式拟合法相比,该方法校正后的灰度图像没有放大噪声,且信噪比提高3.29%,有效地消除了杯状伪影,同时较好地保留了图像边界细节。     

局部扫描情况下多项式拟合的X射线硬化校正

在进行X-CT成像时,容易诱发射束硬化效应。通过多项式拟合建立起多色投影同透射距离的数学模型,然后将多色投影校正为单色投影,是一种简单高效的射束硬化校正方法。对于局部扫描的情况,在重建图像域通过正投影方法计算得到的透射距离不再代表真实的射线穿过长度,拟合数据不再有效。因此借助一圆柱模体,根据圆柱自身的几何特性,通过解析的方法计算得到射线真实的透射距离,并用于射束硬化校正。实验结果表明,该方法能够有效抑制射束硬化引起的图像伪影,提高CT重建图像质量。     

Beam Hardening Correction Base on Monte Carlo Simulation Method

For the empirical beam hardening correction in computerized tomography (CT), it is necessary to measure an attenuation curve for the material. The attenuation curve depends on the X ray machine operation parameters and object material, etc. If any measuring condition changes, a new attenuation curve has to be measured. This approach is time consuming and difficult to implement. A new method of beam hardening correction is presented in this paper, which is based on Monte Carlo simulation of the attenuation characteristic. An aluminium object is scanned and the projection data is corrected by the empirical beam hardening correction and by the simulation based correction. The results of the reconstructed images confirm the correctness of the simulation based method. The simulation based correction has been applied successfully to CT projection data of several test samples, with the material of aluminum, steel and copper.     

基于分段硬化曲线的X射线CT射束硬化校正方法

研究了X射线CT射束硬化的形成机理,分析了射束硬化校正的常用方法,建立了以投影灰度为自变量的射束硬化校正模型,从而降低了射束硬化校正的计算难度。分析了采用多项式拟合射束硬化曲线的优缺点,提出一种基于多项式的分段硬化曲线表达新方法。该方法首先采用过原点的多项式曲线拟合硬化数据,然后通过所得多项式曲线的曲率变化,判断该曲线在拟合区间两端是否出现振荡,并对振荡部分的多项式曲线采用幂函数曲线进行替换,同时保证各段曲线在连接点处C1连续(曲线的C1连续定义为, 两条曲线交于一点且在交点处的一阶导数相等)。计算机CT仿真实验结果表明,该方法对理想CT图像和含噪CT图像的射束硬化校正,均表现出良好的稳定性,并可基本消除射束硬化造成的伪影。     

基于蒙特卡罗模拟的射束硬化校正方法

传统的射束硬化校正方法, 通常需要针对每一种材料测量该材料对射线的吸收曲线. 由于吸收曲线对实验条件有很大的依赖性, 每当改变X光机电压或者被测工件的材料等条件时,需要重新测量吸收曲线才能完成硬化校正过程. 这种方法费事费时. 本文提出了基于蒙特卡罗模拟计算物质吸收曲线的硬化校正方法. 实验中, 分别用本方法和传统的硬化校正方法对铝工件进行硬化校正, 经过比较, 确认本方法是有效的. 然后用该方法对不同材料(铝、铁和铜)的工件进行校正. 实验结果表明, 本方法能有效消除各种材料工件图像中的硬化伪影, 是快速的和切实可行的.     

基于基效应分解的多谱投影序列盲分离算法研究

在常规CT成像系统中,发出的X射线是连续能谱的,导致重建图像出现硬化伪影,影响了材料组分区分,无法进行定量表征。解决这一问题的关键在于实现多能谱CT成像,利用多个窄能谱段或单能量CT图像,提高组分与图像灰度的对应性。相对于传统CT,能谱CT具有更强的组分区分能力,有利于实现物体组分的定量分析。现有的基于光子计数探测器多谱CT在成像时间分辨率和空间分辨率存在局限,基于能谱滤波的多谱CT能谱区分度受限。而基于变电压多谱投影序列盲分离的多谱CT,通过分解连续能谱投影,获取窄能谱投影,进而实现能谱CT成像,确保物质组分与重建图像灰度值的对应性,实用性较强。但是由于X射线能谱和物体组分的未知,在盲分离过程中,衰减系数未知,并且能谱划分是不确定的,导致窄能谱CT重建图像的能量指向性不强,对应能量值与参考能量偏差偏大,影响组分定量分析。因此,针对盲分离中能谱划分不确定性和重建图像能量指向性问题的开展研究。利用衰减系数的光电效应和康普顿效应分解,构建能量约束,消除能量的不确定性,降低分解所得投影重建图像的能量与参考能量值的偏差。在基于以残差的局部方差和最小为优化目标的分解模型中,将分解模型中的衰减系数按光电效应和康普顿效应分解为能量项和材料项,利用能量项的可预知性,依据预先划分的窄能谱段设置其值,固定各分解投影对应的窄能谱段,作为对能量的约束条件。求解所得各分解投影为能量已知投影,对其重建可得到能量确定的各窄能谱段的图像。选择衰减系数相近的硅铝材质构成外硅内铝圆柱体进行实验验证,在有能量约束的求解结果中,硅铝衰减系数与参考值偏差小于无能量约束,所得重建图像中硅铝变化率与理论值趋势较一致,能量指向性强,与参考能量偏差降低。结果表明,所提方法解决了基于变电压序列盲分离多谱CT成像的能量指向问题,能谱分辨率更高,组分表征更准确。     

多金属物体CT图像的金属伪影校正

针对多金属伪影的校正问题,本文通过仿真实验分析了多金属伪影的成因,并提出了一种基于投影校正的多金属伪影校正方法.该方法首先直接从投影域分割出金属区域,然后建立对金属区域投影值的校正模型,最后通过调整模型参数达到校正目的.模型以重建图像的灰度熵为目标函数,采用单纯形法迭代求解使熵最小时的校正参数.仿真和实际数据的实验结果表明,本文算法对多金属伪影的校正起到了良好的效果,且校正后的图像质量优于插值校正法.     

工业CT图像均匀性校正

在工业CT图像重建过程中,射束硬化使得图像出现“杯状”伪影,阵列探测器响应不一致使得图像出现环状伪影、带状伪影和点伪影,影响图像均匀性.本文分析了射束硬化的原理和探测器响应不一致的数学模型,并通过实验,对探测器响应进行多挡板定标得到校正系数表.利用查表插值的方法对投影数据进行均匀性校正,消除上述伪影.     

A statistical iteration approach with energy minimization to sinogram noise reduction for low-dose X-ray CT

Low-dose CT imaging has been particularly used in modern medical practice for its advantage on reducing the radiation dose to patients. However, excessive quantum noise is present in low dose X-ray imaging along with the decrease of the radiation dose; thus, there are obvious streak-like artifacts in reconstructed images. The statistical iterative reconstruction approach applied to the noisy sinogram before a filtered back-projection (FBP) is a resolution to deal with the noisy problem. In this paper, the statistical property of the noise sinogram was considered to achieve a satisfactory image reconstruction and a statistical iterative method with energy minimization was proposed to address the problem of streak-like artifacts. Simulations were performed and indicated that the proposed method could suppress noise and obviously decrease streak-like artifacts in reconstructed images.     

Noise reduction for low-dose X-ray CT based on fuzzy logical in stationary wavelet domain

Apparent streak-like artifacts will present in reconstructed images due to excessive quantum noise in low-dose X-ray imaging process. Dealing with the noisy sinogram before a filtered back-projection (FBP) is a useful solution to solve this noise problem. In this paper, we proposed a novel noise restoration method combining wavelet and fuzzy logical technology for low-dose computed tomography (CT) sinogram. The method first utilizes stationary wavelet transform on the noisy sinogram, namely decomposes the sinogram to different resolution levels. And then, at each decomposed resolution level, a fuzzy shrinkage filter is applied to restore the noise-contaminated wavelet coefficients. Simulations were performed and indicated that the proposed method could significantly suppress noise and reduced streak-like artifacts in reconstructed images while at the same time maintaining the image sharpness.     

Noise reduction for low-dose X-ray computed tomography with fuzzy filter

Low-dose CT imaging has been particularly used in modern medical practice for its advantage on reducing the radiation dose to patients. However, reconstructed images will distinctly degenerate along with the decrease of the radiation dose. A resolution is to deal with the noisy projection space by an effective filter. This study was performed to address this problem and a fuzzy-median filter was proposed in this paper according to the properties of the noise of low-dose CT images. Reconstructed images by FBP were acquired from the previous noisy sinogram filtered by different filters for comparison. This fuzzy-median filter in fact is a spatially variant one that can solve the streak artifacts. And simulations also indicated that this spatially variant filter could suppress noise and obviously decrease streak artifacts in reconstructed images.     

X-ray beam hardening correction for measuring density in linear accelerator industrial computed tomography

Due to X-ray attenuation being approximately proportional to material density, it is possible to measure the inner density through Industrial Computed Tomography (ICT) images accurately. In practice, however, a number of factors including the non-linear effects of beam hardening and diffuse scattered radia-tion complicate the quantitative measurement of density variations in materials. This paper is based on the linearization method of beam hardening correction, and uses polynomial fitting coefficient which is obtained by the curvature of iron polychromatic beam data to fit other materials. Through theoretical deduction, the paper proves that the density measure error is less than 2% if using pre-filters to make the spectrum of linear accelerator range mainly 0.3 MeV to 3 MeV. Experiment had been set up at an ICT system with a 9 MeV electron linear accelerator. The result is satisfactory. This technique makes the beam hardening correction easy and simple, and it is valuable for measuring the ICT density and making use of the CT images to recognize materials.     

3D elemental distribution images in biological samples by XRFµCT

An X‐ray transmission microtomography (CT) system combined with an X‐ray fluorescence microtomography (XRFµCT) system was implemented in the Brazilian Synchrotron Light Laboratory (LNLS), Campinas, Brazil. The aim of this work was to determine the elemental distribution in biological samples (breast, prostate and lung samples) in order to verify the concentration of some elements correlated with characteristics and pathology of each tissue observed by the transmission CT. The experiments were performed at the X‐ray fluorescence beamline (D09B‐XRF) of the Brazilian Synchrotron Light Laboratory, Campinas, Brazil. A quasi‐monochromatic beam produced by a multilayer monochromator was used as an incident beam. The sample was placed on a high‐precision goniometer and translation stages that allow rotating as well as translating it perpendicularly to the beam. The fluorescence photons were collected with an energy dispersive HPGe detector placed at 90° to the incident beam, while transmitted photons were detected with a fast Na(Tl) scintillation counter placed behind the sample on the beam path. The CT images were reconstructed using a filtered‐back projection algorithm and the XRFµCT images were reconstructed using a filtered‐back projection algorithm with absorption corrections. The 3D images were reconstructed using the 3D‐DOCTOR software. Results from the 3D visualization showed that the distribution of iron, copper and zinc is different and heterogeneous from the analyzed samples. Copyright © 2011 John Wiley & Sons, Ltd.     

CT重构中射线硬化的校正研究

在工业CT(ComputedTomography)重构中,由于射束硬化使得重建图像中出现"杯状"伪影。为了消除这种影响,提出了一种校正方法。该方法基于Beer理论,根据多色射束和数据,首先拟合出等效单色射束和数据,然后进行卷积反投影重构。这种方法不仅较好地消除了射线硬化的影响,同时也使重构图像的信息损失不大。     

多通道相位图像的改进型自适应重建算法

自适应重建(Adaptive Reconstruction,AR)算法被广泛应用于磁共振图像的多通道合并问题上.AR算法不需要直接采集各个线圈的灵敏度信息,而是通过通道间信号及噪声相关矩阵,估算出各个通道的灵敏度,从而保证了合并的幅值图像具有较高的信噪比(Signal-to-Noise Ratio,SNR).然而,由于AR算法没有针对相位图像的合并问题进行优化,导致重建出的相位图像具有不确定性.另外,受各通道之间相位偏移及低信噪比相位图像的影响,重建结果可能包含伪影.该文提出了一种改进型AR算法,估算并移除了各通道之间的相位偏移,同时对多通道数据的相位进行质量评估及通道重排,用以进行后续自适应重建.仿体及在体实验表明,该方法可以有效提升AR算法稳定性、消除重建图像中存在的伪影,同时保持合并后幅值图像及相位图像的高信噪比.     

X射线TICT在复合材料工件检测中的射束硬化拟合校正研究

X射线TICT中,X射线透射物质时,发生了能谱硬化现象。使图像重建时出现伪影。因此必须进行修正。文中对X射线硬化现象进行了分析,探讨了X射线TICT在检测复合材料工件中, X射线射束和与透射厚度的关系, 并根据Beer定律和X射线与物质作用的特点, 通过获取X射线射束和数据,首先拟合出射束和与透射厚度的关系式, 然后推导出X射线射束和校正为单色射线射束和的等效厚度与透射厚度的关系及其等效方法, 最终得出X射线TICT在检测复合材料工件中X射线等效单色射线的衰减系数的射束硬化拟合值, 再对此衰减系数拟合值进行卷积反投影重构, 即可有效消除X射线TICT在检测复合材料工件中射束硬化造成的影响。     

一种简便的计算层析系统X射线硬化校正方法

以实物拍摄为依据,用一种最简便的修正方法解决计算机X射线层析术成像时由于硬化效应引起的切片图灰度失真问题。用高性能数字X射线机FAXITRON MX-20(射线管焦点20μm,探测板灰度等级16位)对不同厚度的物体进行透射成像,测得对应的透射光强度,并利用新创的指数拟合法得到理想的拟合曲线,由此推导硬化效应的指数校正公式;最后利用实验室的微型计算机层析设备进行扇形束扫描,并逆投影重建生成计算层析断层图像,验证了该校正方法的实用性。该指数拟合法的误差不到常用的二阶多项式拟合法的1/3,对物体计算层析重构,硬化校正以前有明显的“杯状”伪迹,切片灰度不均匀,用指数法修正以后该伪迹消失,切片灰度均匀。     

X-ray beam hardening correction for measuring density in linear accelerator industrial computed tomography

Due to X-ray attenuation being approximately proportional to material density,it is possible to measure the inner density through Industrial Computed Tomography（ICT） images accurately. In practice,however,a number of factors including the non-linear effects of beam hardening and diffuse scattered radiation complicate the quantitative measurement of density variations in materials. This paper is based on the linearization method of beam hardening correction,and uses polynomial fitting coecient which is obtained by the curvature of iron polychromatic beam data to fit other materials. Through theoretical deduction,the paper proves that the density measure error is less than 2% if using pre-filters to make the spectrum of linear accelerator range mainly 0.3 MeV to 3 MeV. Experiment had been set up at an ICT system with a 9 MeV electron linear accelerator. The result is satisfactory. This technique makes the beam hardening correction easy and simple,and it is valuable for measuring the ICT density and making use of the CT images to recognize materials.