Iterative correction of beam hardening artifacts in CT

Purpose: To reduce beam hardening artifacts in CT in case of an unknown x-ray spectrum and unknown material properties.Methods: The authors assume that the object can be segmented into a few materials with different attenuation coefficients, and parameterize the spectrum using a small number of energy bins. The corresponding unknown spectrum parameters and material attenuation values are estimated by minimizing the difference between the measured sinogram data and a simulated polychromatic sinogram. Three iterative algorithms are derived from this approach: two reconstruction algorithms IGR and IFR, and one sinogram precorrection method ISP.Results: The methods are applied on real x-ray data of a high and a low-contrast phantom. All three methods successfully reduce the cupping artifacts caused by the beam polychromaticity in such a way that the reconstruction of each homogeneous region is to good accuracy homogeneous, even in case the segmentation of the preliminary reconstruction image is poor. In addition, the results show that the three methods tolerate relatively large variations in uniformity within the segments.Conclusions: We show that even without prior knowledge about materials or spectrum, effective beam hardening correction can be obtained.     

Empirical dual energy calibration (EDEC) for cone-beam computed tomography

Material-selective imaging using dual energy CT (DECT) relies heavily on well-calibrated material decomposition functions. These require the precise knowledge of the detected x-ray spectra, and even if they are exactly known the reliability of DECT will suffer from scattered radiation. We propose an empirical method to determine the proper decomposition function. In contrast to other decomposition algorithms our empirical dual energy calibration (EDEC) technique requires neither knowledge of the spectra nor of the attenuation coefficients. The desired material-selective raw data p1 and p2 are obtained as functions of the measured attenuation data q1 and q2 (one DECT scan = two raw data sets) by passing them through a polynomial function. The polynomial's coefficients are determined using a general least squares fit based on thresholded images of a calibration phantom. The calibration phantom's dimension should be of the same order of magnitude as the test object, but other than that no assumptions on its exact size or positioning are made. Once the decomposition coefficients are determined DECT raw data can be decomposed by simply passing them through the polynomial. To demonstrate EDEC simulations of an oval CTDI phantom, a lung phantom, a thorax phantom and a mouse phantom were carried out. The method was further verified by measuring a physical mouse phantom, a half-and-half-cylinder phantom and a Yin-Yang phantom with a dedicated in vivo dual source micro-CT scanner. The raw data were decomposed into their components, reconstructed, and the pixel values obtained were compared to the theoretical values. The determination of the calibration coefficients with EDEC is very robust and depends only slightly on the type of calibration phantom used. The images of the test phantoms (simulations and measurements) show a nearly perfect agreement with the theoretical micro values and density values. Since EDEC is an empirical technique it inherently compensates for scatter components. The empirical dual energy calibration technique is a pragmatic, simple, and reliable calibration approach that produces highly quantitative DECT images.     

Prior image constrained scatter correction in cone-beam computed tomography image-guided radiation therapy

X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.     

Why is TOF PET reconstruction a more robust method in the presence of inconsistent data?

In order to obtain an accurate and quantitative positron emission tomography (PET) image, emission data need to be corrected for random coincidences, photon attenuation and Compton scattering of photons in the tissue, and detector efficiency response or normalization. The accuracy of these corrections strongly affects the quality of the PET image. There is evidence that time-of-flight (TOF) PET reconstruction is less sensitive than non-TOF reconstruction to inconsistencies between emission data and corrections. The purpose of this study is to analyze and discuss such experimental evidence. In this work, inconsistent correction data (inconsistent normalization, absence of scatter correction and mismatched attenuation correction) are introduced in experimental phantom data. Both TOF and non-TOF reconstructed images are analyzed to examine the effect of flawed data. The behavior of TOF reconstruction in respiratory artifacts, a very common example of inconsistency in the data, is studied in patient images. TOF reconstruction is less sensitive to mismatched attenuation correction, erroneous normalization and poorly estimated scatter correction. Such robustness depends strongly on the time resolution of the TOF PET scanner. In particular, the robustness of TOF in the presence of attenuation correction inconsistencies is discussed, using a simulation of a simple model of respiratory artifacts. We expect new generations of PET scanners, with improved time resolution, to be less and less sensitive to poor quality normalization, scatter and attenuation corrections. This not only reduces artifacts in the PET image, but also opens the way to less stringent requirements for the quality of the CT image (reducing either the equipment cost or the dose to the patient), and for the normalization protocols (simplifying or shortening the normalization procedures). Moreover, TOF reconstruction can be beneficial in multimodalities such as PET/MR, where a direct attenuation measurement is not available and attenuation correction can only be approximated.     

The reduction of artifacts due to metal hip implants in CT-attenuation corrected PET images from hybrid PET/CT scanners

CT beam hardening artifacts near metal hip implants may erroneously enhance or diminish radiotracer uptake following CT attenuation correction (AC) of PET images. An artifact reduction algorithm (ARA) was developed to reduce metal artifacts in CT-based AC-PET. The algorithm employed a Bayes classifier to identify beam-hardening artifacts, followed by a partial correction of the attenuation map. ARA was implemented on phantom and patient 18F-FDG studies using a clinical PET/CT scanner. In phantom studies ARA successfully removed two artifacts of erroneously elevated uptake near a stainless steel hip prosthesis which were depicted in the standard CT-AC PET. ARA has also identified two targets absent on the scanner PET images. Target-to-background ratios were 1.5-3 times higher for ARA-PET than scanner images. In a patient study, metal artifacts were of lower intensity in ARA-PET as compared to standard images. Potentially, ARA may improve detectability of small lesions located near metal hip implants.     

Single and dual energy attenuation correction in PET/CT in the presence of iodine based contrast agents

In present positron emission tomography (PET)/computed tomography (CT) scanners, PET attenuation correction is performed by relying on the information given by a single CT scan. The scaling of the linear attenuation coefficients from CT x-ray energy to PET 511 keV gamma energy is prone to errors especially in the presence of CT contrast agents. Attenuation correction based upon two CT scans at different energies but performed at the same time and patient position should reduce such errors and therefore improve the accuracy of the reconstructed PET images at the cost of introduced additional noise. Such CT scans could be provided by future PET/CT scanners that have either dual source CT or energy sensitive CT. Three different dual energy scaling methods for attenuation correction are introduced and assessed by measurements with a modified NEMA 1994 phantom with different CT contrast agent concentrations. The scaling is achieved by differentiating between (1) Compton and photoelectric effect, (2) atomic number and density, or (3) water-bone and water-iodine scaling schemes. The scaling method (3) is called hybrid dual energy computed tomography attenuation correction (hybrid DECTAC). All three dual energy scaling methods lead to a reduction of contrast agent artifacts with respect to single energy scaling. The hybrid DECTAC method resulted in PET images with the weakest artifacts. Both, the hybrid DECTAC and Compton/photoelectric effect scaling resulted also in images with the lowest PET background variability. Atomic number/density scaling and Compton/photoelectric effect scaling had problems to correctly scale water, hybrid DECTAC scaling and single energy scaling to correctly scale Teflon. Atomic number/density scaling and hybrid DECTAC could be generalized to reduce these problems.     

A simple, direct method for x-ray scatter estimation and correction in digital radiography and cone-beam CT

X-ray scatter poses a significant limitation to image quality in cone-beam CT (CBCT), resulting in contrast reduction, image artifacts, and lack of CT number accuracy. We report the performance of a simple scatter correction method in which scatter fluence is estimated directly in each projection from pixel values near the edge of the detector behind the collimator leaves. The algorithm operates on the simple assumption that signal in the collimator shadow is attributable to x-ray scatter, and the 2D scatter fluence is estimated by interpolating between pixel values measured along the top and bottom edges of the detector behind the collimator leaves. The resulting scatter fluence estimate is subtracted from each projection to yield an estimate of the primary-only images for CBCT reconstruction. Performance was investigated in phantom experiments on an experimental CBCT bench-top, and the effect on image quality was demonstrated in patient images (head, abdomen, and pelvis sites) obtained on a preclinical system for CBCT-guided radiation therapy. The algorithm provides significant reduction in scatter artifacts without compromise in contrast-to-noise ratio (CNR). For example, in a head phantom, cupping artifact was essentially eliminated, CT number accuracy was restored to within 3%, and CNR (breast-to-water) was improved by up to 50%. Similarly in a body phantom, cupping artifact was reduced by at least a factor of 2 without loss in CNR. Patient images demonstrate significantly increased uniformity, accuracy, and contrast, with an overall improvement in image quality in all sites investigated. Qualitative evaluation illustrates that soft-tissue structures that are otherwise undetectable are clearly delineated in scatter-corrected reconstructions. Since scatter is estimated directly in each projection, the algorithm is robust with respect to system geometry, patient size and heterogeneity, patient motion, etc. Operating without prior information, analytical modeling, or Monte Carlo, the technique is easily incorporated as a preprocessing step in CBCT reconstruction to provide significant scatter reduction.     

Attenuation correction for small animal PET tomographs

Attenuation correction is one of the important corrections required for quantitative positron emission tomography (PET). This work will compare the quantitative accuracy of attenuation correction using a simple global scale factor with traditional transmission-based methods acquired either with a small animal PET or a small animal x-ray computed tomography (CT) scanner. Two phantoms (one mouse-sized and one rat-sized) and two animal subjects (one mouse and one rat) were scanned in CTI Concorde Microsystem's microPET Focus for emission and transmission data and in ImTek's MicroCAT II for transmission data. PET emission image values were calibrated against a scintillation well counter. Results indicate that the scale factor method of attenuation correction places the average measured activity concentration about the expected value, without correcting for the cupping artefact from attenuation. Noise analysis in the phantom studies with the PET-based method shows that noise in the transmission data increases the noise in the corrected emission data. The CT-based method was accurate and delivered low-noise images suitable for both PET data correction and PET tracer localization.     

基于支持向量回归的PET/CT图像衰减校正方法

目的在电子发射及计算机断层扫描系统(positron emission computed tomography/X-ray computed tomography,PET/CT)图像衰减校正的能量转换过程中,为了改进双线性转换法用线性关系来拟合非线性关系的不足,本文以支持向量回归为基础,提出了一种新的能量转换法即支持向量回归的PET/CT图像衰减校正方法来进行衰减校正,以寻找CT值和511 keV能量下线性衰减系数值之间的最佳转换关系。方法使用仿真软件GATE(Geant4 Application Tomographic Emission)模拟了11组不同材质的圆柱体体模。然后根据GATE仿真的不同材质圆柱体体模,求出其CT值和511 keV能量下线性衰减系数值并代入SVR模型中进行训练,建立CT值和511 keV能量下线性衰减系数值之间的SVR模型。最后与目前PET/CT衰减校正能量转换中常用的双线性能量转换法进行对比分析,并分别应用于GATE仿真的NCAT(NURBs Cardiac Torso)像素体模图像中,评估两种方法准确性的差异。结果支持向量回归的PET/CT图像衰减校正方法得到的511 keV能量下对应物质的线性衰减系数值的相对百分误差值较小(肺的相对百分误差值3.1%和肝脏的相对百分误差值1.08%),且经过支持向量回归法衰减校正的PET图像,其MSE评价值都是最小的(176.9230),其PSNR和AG的评价值都是最大的(31.8621和7.9083)。这说明经过支持向量回归法衰减校正的PET图像相比于双线性转换法衰减校正的PET图像,更接近于静态的图像。结论支持向量回归的PET/CT图像衰减校正方法在PET/CT图像的衰减校正应用中有更好的表现,可以更好地吻合CT值与511 keV能量下线性衰减系数之间的转换关系,从而提高了PET/CT图像的衰减校正效果,改善了PET/CT图像定量的准确性,便于医生做出更精确的临床诊断。     

Attenuation correction for three-dimensional PET using uncollimated flood-source transmission measurements

An attenuation-correction method for three-dimensional PET imaging, which obtains attenuation-correction factors from transmission measurements using an uncollimated flood source, is described. This correction is demonstrated for two different phantoms using transmission data acquired with QPET, a rotating imaging system with two planar detectors developed for imaging small volumes. The scatter amplitude in the transmission projections was a maximum of 30%; to obtain accurate attenuation-correction factors the scatter distribution was first calculated and subtracted. The attenuation-corrected emission images for both phantoms indicate that their original uniform amplitudes have been restored. The attenuation correction adds only a small amount of noise to the emission images, as evaluated from the standard deviation over a central region. For the first phantom, with maximum attenuation of 48%, the noise added was 2.6%. The second phantom was attenuated by a maximum of 37%, and 1.9% noise was added. Because the transmission data are smoothed, some artifacts are visible at the edges of the phantom where the correction factors change abruptly within the emission image.     

Calibration of megavoltage cone-beam CT for radiotherapy dose calculations: correction of cupping artifacts and conversion of CT numbers to electron density

Megavoltage cone-beam CT (MV CBCT) is used for three-dimensional imaging of the patient anatomy on the treatment table prior to or just after radiotherapy treatment. To use MV CBCT images for radiotherapy dose calculation purposes, reliable electron density (ED) distributions are needed. Patient scatter, beam hardening and softening effects result in cupping artifacts in MV CBCT images and distort the CT number to ED conversion. A method based on transmission images is presented to correct for these effects without using prior knowledge of the object's geometry. The scatter distribution originating from the patient is calculated with pencil beam scatter kernels that are fitted based on transmission measurements. The radiological thickness is extracted from the scatter subtracted transmission images and is then converted to the primary transmission used in the cone-beam reconstruction. These corrections are performed in an iterative manner, without using prior knowledge regarding the geometry and composition of the object. The method was tested using various homogeneous and inhomogeneous phantoms with varying shapes and compositions, including a phantom with different electron density inserts, phantoms with large density variations, and an anthropomorphic head phantom. For all phantoms, the cupping artifact was substantially removed from the images and a linear relation between the CT number and electron density was found. After correction the deviations in reconstructed ED from the true values were reduced from up to 0.30 ED units to 0.03 for the majority of the phantoms; the residual difference is equal to the amount of noise in the images. The ED distributions were evaluated in terms of absolute dose calculation accuracy for homogeneous cylinders of different size; errors decreased from 7% to below 1% in the center of the objects for the uncorrected and corrected images, respectively, and maximum differences were reduced from 17% to 2%, respectively. The presented method corrects the MV CBCT images for cupping artifacts and extracts reliable ED information of objects with varying geometries and composition, making these corrected MV CBCT images suitable for accurate dose calculation purposes.     

A preliminary study of neuroSPECT evaluation of patients with post-traumatic smell impairment

Background

Attenuation correction is generally used to PET images to achieve count rate values independent from tissue densities. The goal of this study was to provide a qualitative comparison of attenuation corrected PET images produced by a PET-CT device (CT, 120 kV, 40 mAs, FOV 600 mm) with and without segmentation of transmission data (ACseg⁺ and ACseg^-respectively). Methods: The reconstructed images were compared to attenuation corrected images obtained with a high-energy transmission source (Cs-137 – 662 keV). Thirty oncologic patients were studied using CT and ¹³⁷Cs for attenuation correction. All image data were acquired using the Gemini PET-CT scanner (Philips Medical Systems). It is an open PET-CT system that consists of the MX8000 multislice CT and the Allegro PET scanner arranged in a separable configuration. Images with ACseg⁺ and ACseg^- were analyzed simultaneously in coronal, sagittal and transaxial planes. Two nuclear medicine physicians reviewed the image sets. Results: The image quality in the area of metal implants was better with ACseg⁺ than ACseg^-, without metal induced artifacts generally observed in CT corrected images. Further the images with ACseg⁺ were qualitatively comparable to those obtained with ¹³⁷Cs attenuation correction. Conclusions: In case of metal implants, PET studies corrected by CT should preferably use the ACseg⁺ method to avoid the image artifacts.     

Attenuation correction of four dimensional (4D) PET using phase-correlated 4D-computed tomography

The image quality in a conventional positron emission tomography (PET)/computed tomography (CT) scanner is degraded by respiratory motion because of erroneous attenuation correction when three-dimensional image acquisition is used. To overcome this problem, time-resolved data acquisition (4D) is required. For this, a Siemens Biograph 16 PET/CT scanner has been modified and its normal capability has been extended to a true 4D-PET/4D-CT imaging device including phase-correlated attenuation correction. To verify the correct functionality of this device, experiments on a respiratory motion phantom that allowed movement in two dimensions have been performed. The measurements showed good spatial correlation as well as good time synchronization between the PET and CT data. Furthermore, the motion pattern of the phantom and the shape of the activity distribution have been examined, and the volume of the reconstructed PET images has been analyzed. The results demonstrate the feasibility of such a procedure, and we therefore recommend that 4D-PET data should be reconstructed using 4D-CT data, which can be acquired on the same machine.     

Correction of megavoltage cone-beam CT images for dose calculation in the head and neck region

Megavoltage cone-beam computed tomography (MVCBCT) imaging systems are now available for image-guided radiation therapy delivery and verification. In order to use the three-dimensional anatomical information for dose calculation, the MVCBCT image must provide accurate electron density. This work proposes a new method that has been developed to correct for the cupping and missing data artifacts seen on MVCBCT images of the head and neck region. It uses a conventional kilovoltage CT (kVCT) image as a reference for electron density and rigid registration with a MVCBCT image to obtain correction factors. Dose calculations performed on MVCBCT images corrected with the proposed method agree with calculations done on kVCT images within +/- 1% on phantoms. With patients images the agreement is within +/- 13% above the shoulders and +/- 5% below the shoulder line. This level of dose calculation accuracy allows the use of MVCBCT images for dose verification purposes.     

基于旋转准直器的锥形束CT散射矫正方法

针对锥形束CT（CBCT）图像质量受散射影响比较严重的情况,提出一种基于旋转准直器的CBCT散射矫正方法。该方法在射线源和模体之间放置一个圆形的旋转准直器,并通过准直器的旋转使透过准直器的射线不断沿轴向来回扫描,以获取整个容积图像的投影图像信息,然后利用投影图像的遮挡区域估计整幅图像的散射信息并将其从投影图像中去除,最后利用改进FDK算法重建图像。结果表明,与CBCT图像相比,散射矫正后的重建图像CBCT值的均方根误差从16.00%下降为1.18%,杯状伪影从14.005%下降为0.660%,峰值信噪比从16.959 4提高到31.450 0。CBCT图像质量得到明显提高。     

Phased attenuation correction in respiration correlated computed tomography/positron emitted tomography

The motion of lung tumors with respiration causes difficulties in the imaging with computed tomography (CT) and positronemitted tomography (PET). Since an accurate knowledge of the position of the tumor and the surrounding tissues is needed for radiation treatment planning, it is important to improve CT/PET image acquisition. The purpose of this study was to evaluate the potential to improve image acquisition using phased attenuation correction in respiration correlated CT/PET, where data of both modalities were binned retrospectively. Respiration correlated scans were made on a Siemens Biograph Sensation 16 CT/PET scanner which was modified to make a low pitch CT scan and list mode PET scan possible. A lollipop phantom was used in the experiments. The sphere with a diameter of 3.1 cm was filled with approximately 20 MBq 18F-FDG. Three longitudinal movement amplitudes were tested: 2.5, 3.9, and 4.8 cm. After collection of the raw CT data, list mode PET data, and the respiratory signal CT/PET images were binned to ten phases with the help of in-house-built software. Each PET phase was corrected for attenuation with CT data of the corresponding phase. For comparison, the attenuation correction was also performed with nonrespiration correlated (non-RC) CT data. The volume and the amplitude of the movement were calculated for every phaseof both the CT and PET data (with phased attenuation correction). Maximum and average activity concentrations were compared between the phased and nonphased attenuation corrected PET. With a standard non-RC CT/PET scan, the volume was underestimated by as much as 46% in CT and the PET volume was overestimated to 370%. The volumes found with RC-CT/PET scanning had average deviations of 1.9% (+/- 4.8%) and 1.5% (+/- 3.4%) from the actual volume, for the CT and PET volumes, respectively. Evaluation of the maximum activity concentration showed a clear displacement in the images with non-RC attenuation correction, and activity values were on average14% (+/- 12%) lower than with phased attenuation correction. The standard deviation of the maximum activity values found in the different phases was a factor of 10 smaller when phased attenuation correction was applied. In this phantom study, we have shown that a combination of respiration correlated CT/PET scanning with application of phased attenuation correction can improve the imaging of moving objects and can lead to improved volume estimation and a more precise localization and quantification of the activity.     

Segmentation-free statistical image reconstruction for polyenergetic x-ray computed tomography with experimental validation

This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications.     

Fuzzy clustering-based segmented attenuation correction in whole-body PET imaging

Segmented attenuation correction is now a widely accepted technique to reduce noise propagation from transmission scanning in positron emission tomography (PET). In this paper, we present a new method for segmenting transmission images in whole-body scanning. This reduces the noise in the correction maps while still correcting for differing attenuation coefficients of specific tissues. Based on the fuzzy C-means (FCM) algorithm, the method segments the PET transmission images into a given number of clusters to extract specific areas of differing attenuation such as air, the lungs and soft tissue, preceded by a median filtering procedure. The reconstructed transmission image voxels are, therefore, segmented into populations of uniform attenuation based on knowledge of the human anatomy. The clustering procedure starts with an overspecified number of clusters followed by a merging process to group clusters with similar properties (redundant clusters) and removal of some undesired substructures using anatomical knowledge. The method is unsupervised, adaptive and allows the classification of both pre- or post-injection transmission images obtained using either coincident 68Ge or single-photon 137Cs sources into main tissue components in terms of attenuation coefficients. A high-quality transmission image of the scanner bed is obtained from a high statistics scan and added to the transmission image. The segmented transmission images are then forward projected to generate attenuation correction factors to be used for the reconstruction of the corresponding emission scan. The technique has been tested on a chest phantom simulating the lungs, heart cavity and the spine, the Rando-Alderson phantom, and whole-body clinical PET studies showing a remarkable improvement in image quality, a clear reduction of noise propagation from transmission into emission data allowing for reduction of transmission scan duration. There was very good correlation (R2 = 0.96) between maximum standardized uptake values (SUVs) in lung nodules measured on images reconstructed with measured and segmented attenuation correction with a statistically significant decrease in SUV (17.03% +/- 8.4%, P < 0.01) on the latter images, whereas no proof of statistically significant differences on the average SUVs was observed. Finally, the potential of the FCM algorithm as a segmentation method and its limitations as well as other prospective applications of the technique are discussed.     

Cone beam volume CT image artifacts caused by defective cells in x-ray flat panel imagers and the artifact removal using a wavelet-analysis-based algorithm

The application of x-ray flat panel imagers (FPIs) in cone beam volume CT (CBVCT) has attracted increasing attention. However, due to a deficient semiconductor array manufacturing process, defective cells unavoidably exist in x-ray FPIs. These defective cells cause their corresponding image pixels in a projection image to behave abnormally in signal gray level, and result in severe streak and ring artifacts in a CBVCT image reconstructed from the projection images. Since a three-dimensional (3-D) back-projection is involved in CBVCT, the formation of the streak and ring artifacts is different from that in the two-dimensional (2-D) fan beam CT. In this paper, a geometric analysis of the abnormality propagation in the 3D back-projection is presented, and the morphology of the streak and ring artifacts caused by the abnormality propagation is investigated through both computer simulation and phantom studies. In order to calibrate those artifacts, a 2D wavelet-analysis-based statistical approach to correct the abnormal pixels is proposed. The approach consists of three steps: (1) the location-invariant defective cells in an x-ray FPI are recognized by applying 2-D wavelet analysis on flat-field images, and a comprehensive defective cell template is acquired; (2) based upon the template, the abnormal signal gray level of the projection image pixels corresponding to the location-invariant defective cells is replaced with the interpolation of that of their normal neighbor pixels; (3) that corresponding to the isolated location-variant defective cells are corrected using a narrow-windowed median filter. The CBVCT images of a CT low-contrast phantom are employed to evaluate this proposed approach, showing that the streak and ring artifacts can be reliably eliminated. The novelty and merit of the approach are the incorporation of the wavelet analysis whose intrinsic multi-resolution analysis and localizability make the recognition algorithm robust under variable x-ray exposure levels between 30% and 70% of the dynamic range of an x-ray FPI.     

An iterative approach to the beam hardening correction in cone beam CT

In computed tomography (CT), the beam hardening effect has been known to be one of the major sources of deterministic error that leads to inaccuracy and artifact in the reconstructed images. Because of the polychromatic nature of the x-ray source used in CT and the energy-dependent attenuation of most materials, Beer's law no longer holds. As a result, errors are present in the acquired line integrals or measurements of the attenuation coefficients of the scanned object. In the past, many studies have been conducted to combat image artifacts induced by beam hardening. In this paper, we present an iterative beam hardening correction approach for cone beam CT. An algorithm that utilizes a tilted parallel beam geometry is developed and subsequently employed to estimate the projection error and obtain an error estimation image, which is then subtracted from the initial reconstruction. A theoretical analysis is performed to investigate the accuracy of our methods. Phantom and animal experiments are conducted to demonstrate the effectiveness of our approach.