High-quality 3D correction of ring and radiant artifacts in flat panel detector-based cone beam volume CT imaging

The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.     

Tomographic motion detection and correction directly in sinogram space

Patient motion, especially respiratory motion, results in various artefacts such as blurring and streaks in tomographic images. The interplay of the movement of the beam aperture and variations of organ anatomy during delivery can create 'hot' and 'cold' spots throughout the field in intensity-modulated radiation therapy (IMRT). Detection and correction of patient motion is extremely important in tomographic imaging and IMRT. Tomographic projection data (sinogram) encode not only the patient anatomy information, but also the intra-scanning motion information. In this paper, we developed an algorithm to detect and correct the in-plane respiratory motion directly in sinogram space. The respiratory motion is modelled as time-varying scaling along the x and y directions. Its effects on the sinogram are discussed. Based on the traces of some nodal points in the sinogram, the intra-scanning motion is determined. The motion correction is also implemented in sinogram space. The motion-corrected sinogram is used for reconstruction by the filtered back-projection (FBP) method. Computer simulations validate the motion detection and correction algorithm. The reconstructed images from the motion-corrected sinogram eliminate the majority of the artefacts. The method could be applied to projection data used in CT and ECT, as well as in tomotherapy delivery modification and dose reconstruction.     

Removal of ring artifacts in computed tomographic imaging using iterative center weighted median filter

A new iterative center weighted median filter (ICWMF) for ring artifact reduction from the micro-computed tomographic (μ-CT) image is proposed in this paper. The center weight of the median filter is computed based on the characteristic of the ring artifact in the mean curve of the projection data. The filter operates on the deviation of the mean curve to smooth the ring generating peaks and troughs iteratively while preserving the details due to image. A convergence criterion for the iterative algorithm is determined from the distribution of the local deviation computed from the mean curve deviation. The estimate of the mean curve obtained using the ICWMF is used to correct the ring corrupted projection data from which reconstruction gives the ring artifact suppressed μ-CT image. Test results on both the synthetic and real images demonstrate that the ring artifacts can be more effectively suppressed using our method as compared to other ring removal techniques reported in the literature.     

Characterization and correction of temporal artifacts in CT

Image artifacts, caused by a temporally delayed response of a computed tomography (CT) detector, were investigated. To study its consequences, a computer model for a standard third generation CT scanner was devised and simulations were carried out. Resulting image artifacts were studied for various voxel-based and mathematical phantoms using three time constants, which characterize the delayed signal responses of different detector configurations. Furthermore, a theory was developed to understand temporal artifacts in reconstructed images. A filter function was derived, which compensates for temporal artifacts. For a given phantom, simulations and theory demonstrate that artifacts scale with the time constant, characteristic for the detector, and the angular speed of the scanner.     

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.     

Reduction of motion blurring artifacts using respiratory gated CT in sinogram space: a quantitative evaluation

Techniques have been developed for reducing motion blurring artifacts by using respiratory gated computed tomography (CT) in sinogram space and quantitatively evaluating the artifact reduction. A synthetic sinogram was built from multiple scans intercepting a respiratory gating window. A gated CT image was then reconstructed using the filtered back-projection algorithm. Wedge phantoms, developed for quantifying the motion artifact reduction, were scanned while being moved using a computer-controlled linear stage. The resulting artifacts appeared between the high and low density regions as an apparent feature with a Hounsfield value that was the average of the two regions. A CT profile through these regions was fit using two error functions, each modeling the partial-volume averaging characteristics for the unmoving phantom. The motion artifact was quantified by determining the apparent distance between the two functions. The blurring artifact had a linear relationship with both the speed and the tangent of the wedge angles. When gating was employed, the blurring artifact was reduced systematically at the air-phantom interface. The gated image of phantoms moving at 20 mm/s showed similar blurring artifacts as the nongated image of phantoms moving at 10 mm/s. Nine patients were also scanned using the synchronized respiratory motion technique. Image artifacts were evaluated in the diaphragm, where high contrast interfaces intercepted the imaging plane. For patients, this respiratory gating technique reduced the blurring artifacts by 9%-41% at the lung-diaphragm interface.     

一种快速校正CT环形伪影的方法

背景：环形伪影严重影响了CT图像质量,对图像后处理造成困难以及容易造成误诊断。目前去除环形伪影必不可少。 目的：去除CT重建图像中的环形伪影,提高CT图像质量以及后续处理和量化分析的精度,便于诊断。 方法：首先把含环形伪影的CT图像进行线性变换,将灰度图像转换成浮点类型的图像。接着由直角坐标变换到极坐标,这样原来的环形伪影就被变换成线形伪影。设计多维滤波器,计算每个象素滤波后均值以及方差,通过与阈值比较确定伪影范围。最后通过对伪影范围进行修正以及对图像进行坐标变换,变为灰度图像。 结果与结论：通过Matlab 7.0软件设计程序,处理含环形伪影的CT图像。实验表明,此方法能有效快速地校正CT环形伪影,是一种属于图像后处理的校正方法。     

Classification of ring artifacts for their effective removal using type adaptive correction schemes

High resolution tomographic images acquired with a digital X-ray detector are often degraded by the so called ring artifacts. In this paper, a detail analysis including the classification, detection and correction of these ring artifacts is presented. At first, a novel idea for classifying rings into two categories, namely type I and type II rings, is proposed based on their statistical characteristics. The defective detector elements and the dusty scintillator screens result in type I ring and the mis-calibrated detector elements lead to type II ring. Unlike conventional approaches, we emphasize here on the separate detection and correction schemes for each type of rings for their effective removal. For the detection of type I ring, the histogram of the responses of the detector elements is used and a modified fast image inpainting algorithm is adopted to correct the responses of the defective pixels. On the other hand, to detect the type II ring, first a simple filtering scheme is presented based on the fast Fourier transform (FFT) to smooth the sum curve derived form the type I ring corrected projection data. The difference between the sum curve and its smoothed version is then used to detect their positions. Then, to remove the constant bias suffered by the responses of the mis-calibrated detector elements with view angle, an estimated dc shift is subtracted from them. The performance of the proposed algorithm is evaluated using real micro-CT images and is compared with three recently reported algorithms. Simulation results demonstrate superior performance of the proposed technique as compared to the techniques reported in the literature.     

Extension of the reconstruction field of view and truncation correction using sinogram decomposition

We propose a novel truncation correction algorithm that completes unmeasured data outside of the scan field of view, which allows extending the reconstruction field of view. When a patient extends outside the detector coverage the projection data are transversely truncated, which causes severe artifacts. The proposed method utilizes the idea of sinogram decomposition, where we consider sinogram curves corresponding to image points outside the field of view. We propose two ways to estimate the truncated data, one based on the minimum value along the sinogram curve, and the other based on the data values near the edge of truncation. Both estimation methods are combined to achieve uniform image quality improvement from the edge of truncation to the outer side of the extended region. In our evaluation with simulated and real projection data we compare the proposed method with existing methods and investigate the dependence on the amount of truncation. The evaluation shows that the proposed method handles cases when truncation is present on both sides of the detector, or when a high-contrast object is located outside the field of view.     

能谱CT成像中测量位置与校正系数的关系

BACKGROUND: In spectral CT imaging study, the selection of scanning parameters is considered by most researchers, but the effects of measuring position are often overlooked. Actual measurement found that different measurement location had significant impact on the result of the measurement. Through measurement and mathematical model of a large amount of data, we can correct the measurement results of different location. The results with real data alignment are higher.     

Efficient correction for CT image artifacts caused by objects extending outside the scan field of view

The purpose of this paper is to develop a method of eliminating CT image artifacts generated by objects extending outside the scan field of view, such as obese or inadequately positioned patients. CT projection data are measured only within the scan field of view and thus are abruptly discontinuous at the projection boundaries if the scanned object extends outside the scan field of view. This data discontinuity causes an artifact that consists of a bright peripheral band that obscures objects near the boundary of the scan field of view. An adaptive mathematical extrapolation scheme with low computational expense was applied to reduce the data discontinuity prior to convolution in a filtered backprojection reconstruction. Despite extended projection length, the convolution length was not increased and thus the reconstruction time was not affected. Raw projection data from ten patients whose bodies extended beyond the scan field of view were reconstructed using a conventional method and our extended reconstruction method. Limitations of the algorithm are investigated and extensions for further improvement are discussed. The images reconstructed by conventional filtered backprojection demonstrated peripheral bright-band artifacts near the boundary of the scan field of view. Images reconstructed with our technique were free of such artifacts and clearly showed the anatomy at the periphery of the scan field of view with correct attenuation values. We conclude that bright-band artifacts generated by obese patients whose bodies extend beyond the scan field of view were eliminated with our reconstruction method, which reduces boundary data discontinuity. The algorithm can be generalized to objects with inhomogeneous peripheral density and to true "Region of Interest Reconstruction" from truncated projections.     

Method for transforming CT images for attenuation correction in PET/CT imaging

A tube-voltage-dependent scheme is presented for transforming Hounsfield units (HU) measured by different computed tomography (CT) scanners at different x-ray tube voltages (kVp) to 511 keV linear attenuation values for attenuation correction in positron emission tomography (PET) data reconstruction. A Gammex 467 electron density CT phantom was imaged using a Siemens Sensation 16-slice CT, a Siemens Emotion 6-slice CT, a GE Lightspeed 16-slice CT, a Hitachi CXR 4-slice CT, and a Toshiba Aquilion 16-slice CT at kVp ranging from 80 to 140 kVp. All of these CT scanners are also available in combination with a PET scanner as a PET/CT tomograph. HU obtained for various reference tissue substitutes in the phantom were compared with the known linear attenuation values at 511 keV. The transformation, appropriate for lung, soft tissue, and bone, yields the function 9.6 x 10(-5). (HU+ 1000) below a threshold of approximately 50 HU and a (HU+ 1000)+b above the threshold, where a and b are fixed parameters that depend on the kVp setting. The use of the kVp-dependent scaling procedure leads to a significant improvement in reconstructed PET activity levels in phantom measurements, resolving errors of almost 40% otherwise seen for the case of dense bone phantoms at 80 kVp. Results are also presented for patient studies involving multiple CT scans at different kVp settings, which should all lead to the same 511 keV linear attenuation values. A linear fit to values obtained from 140 kVp CT images using the kVp-dependent scaling plotted as a function of the corresponding values obtained from 80 kVp CT images yielded y = 1.003 x -0.001 with an R2 value of 0.999, indicating that the same values are obtained to a high degree of accuracy.     

Accuracy of CT-based attenuation correction in PET/CT bone imaging

We evaluate the accuracy of scaling CT images for attenuation correction of PET data measured for bone. While the standard tri-linear approach has been well tested for soft tissues, the impact of CT-based attenuation correction on the accuracy of tracer uptake in bone has not been reported in detail. We measured the accuracy of attenuation coefficients of bovine femur segments and patient data using a tri-linear method applied to CT images obtained at different kVp settings. Attenuation values at 511 keV obtained with a (68)Ga/(68)Ge transmission scan were used as a reference standard. The impact of inaccurate attenuation images on PET standardized uptake values (SUVs) was then evaluated using simulated emission images and emission images from five patients with elevated levels of FDG uptake in bone at disease sites. The CT-based linear attenuation images of the bovine femur segments underestimated the true values by 2.9 ± 0.3% for cancellous bone regardless of kVp. For compact bone the underestimation ranged from 1.3% at 140 kVp to 14.1% at 80 kVp. In the patient scans at 140 kVp the underestimation was approximately 2% averaged over all bony regions. The sensitivity analysis indicated that errors in PET SUVs in bone are approximately proportional to errors in the estimated attenuation coefficients for the same regions. The variability in SUV bias also increased approximately linearly with the error in linear attenuation coefficients. These results suggest that bias in bone uptake SUVs of PET tracers ranges from 2.4% to 5.9% when using CT scans at 140 and 120 kVp for attenuation correction. Lower kVp scans have the potential for considerably more error in dense bone. This bias is present in any PET tracer with bone uptake but may be clinically insignificant for many imaging tasks. However, errors from CT-based attenuation correction methods should be carefully evaluated if quantitation of tracer uptake in bone is important.     

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.     

An experimental study on the noise properties of x-ray CT sinogram data in Radon space

Computed tomography (CT) has been well established as a diagnostic tool through hardware optimization and sophisticated data calibration. For screening purposes, the associated x-ray exposure risk must be minimized. An effective way to minimize the risk is to deliver fewer x-rays to the subject or lower the mAs parameter in data acquisition. This will increase the data noise. This work aims to study the noise property of the calibrated or preprocessed sinogram data in Radon space as the mAs level decreases. An anthropomorphic torso phantom was scanned repeatedly by a commercial CT imager at five different mAs levels from 100 down to 17 (the lowest value provided by the scanner). The preprocessed sinogram datasets were extracted from the CT scanner to a laboratory computer for noise analysis. The repeated measurements at each mAs level were used to test the normality of the repeatedly measured samples for each data channel using the Shapiro-Wilk statistical test merit. We further studied the probability distribution of the repeated measures. Most importantly, we validated a theoretical relationship between the sample mean and variance at each channel. It is our intention that the statistical test and particularly the relationship between the first and second statistical moments will improve low-dose CT image reconstruction for screening applications.     

Removal of ocular artifacts from the REM sleep EEG.

The present report concerns the first study in which electrooculographic (EOG) contamination of electroencephalographic (EEG) recordings in rapid eye movement (REM) sleep is systematically investigated. Contamination of REM sleep EEG recordings in six subjects was evaluated in the frequency domain. REM-active and REM-quiet series were obtained for each subject. Transfer coefficients and power spectra of EOG and EEG indicated that (a) increases in transfer coefficients beyond 4.5 Hz are brought about by residual EEG in the EOG, and (b) EOG-EEG contamination in the delta band is most pronounced in frontal, intermediate in central and negligible in occipital leads. It was found that correction of the REM-active series resulted in significant (c) reductions in power, (d) increases in interhemispheric coherences and (e) reductions in degree of lateral asymmetry. These effects were largest for frontal leads, but still marked for central ones. The results are discussed in the light of previous findings concerning models of hemispheric functioning during REM sleep.     

能谱CT金属伪影消除技术和骨算法成像消减脊柱金属内固定物伪影的对比研究

目的 探讨能谱CT金属伪影消除(MARs)技术与普通CT骨算法重建在消减脊柱内固定术后伪影的价值。方法 回顾性分析2013年2月—2014年2月解放军第一一七医院22例行脊柱金属内固定置入患者的影像学资料。其中男14例、女8例,年龄30～77岁。22例患者术后不同时间分别行能谱CT MARs技术检查(MARs组)、骨算法成像检查(骨算法组)。测量并计算各组感兴趣区的伪影指数(AI),采用骨窗图像质量主观评估标准对骨窗图像质量进行评分,比较MARs组和骨算法组患者骨窗图像质量评分情况,以及不同单能量值MARs组和骨算法组间AI的分布差异。结果 MARs组中,随着单能量值的减低,AI值逐渐增高。MARs组各单能量值和骨算法组间比较,AI值差异有统计学意义(F=8.696, P<0.05);进一步组间LSD-t检验显示,在60~140 keV条件下,MARs组AI值均小于骨算法组,差异均有统计学意义(P值均<0.05)。骨窗图像质量评分比较,骨算法组(2.81±0.39)分,优于MARs组(2.00±0.53)分,差异有统计学意义(t=4.856, P<0.01)。结论 能谱CT MARs技术和骨算法成像对消减脊柱金属内固定伪影各有优点,应当结合临床需要选择合适的CT成像技术。     

Correcting organ motion artifacts in x-ray CT medical imaging systems by adaptive processing. I. Theory

X-ray CT scanners provide images of transverse cross sections of the human body from a large number of projections. During the data acquisition process, which usually takes about 1 s, motion effects such as respiration, cardiac motion, and patient restlessness produce artifacts that appear as blurring, doubling, and distortion in the reconstructed images, and may lead to inaccurate diagnosis. To address this problem several processing techniques have been proposed that require a priori knowledge of the motion characteristics. This paper proposes a method, which makes no assumptions about the properties of the motion, to eliminate the motion artifacts. The approach in this paper uses a spatial overlap correlator scheme to accurately track organ motion in computed tomography imaging systems. Then, it is shown that as optimum processing scheme to remove organ motion effects is to apply adaptive interference cancellation (AIC) methods, which treat the output of the spatial overlap correlator as noise interference at the input of the AIC process. Furthermore, an AIC method does not require any kind of periodicity of the motion effects. Synthetic data tests demonstrate the validity of this approach and show that hardware modifications are essential for its implementation in x-ray CT medical imaging systems.     

Automatic detection of linear artifacts in medical images

Our purpose in this study is to describe an algorithm for the automatic detection of linear artifacts in medical images. Linear artifacts arise as a result of many different forms of tissues and tissue boundaries within the imaging volume. Additionally, linear artifacts can arise for artificial structures such as radioactive seeds and radioactive linear sources. It is the purpose of the described algorithm to automatically detect linear artifacts of a certain length and diameter. The algorithm was written and compiled on a Pentium-4 based computer in the Microsoft Visual C/C++ language. Inert coils supplied by Radiomed Inc. were implanted into a standard prostate ultrasound phantom. Transaxial ultrasound images of the implanted phantom were obtained at 2 mm increments. The coded algorithm was then applied to the ultrasound imaging volume to automatically segment out the implanted coils. Thirteen coils were implanted in the prostate phantom. Thirteen coils were automatically identified in the imaging volume. An algorithm was developed to automatically determine the position and orientation of radioactive coils within an imaging volume. The algorithm successfully identified thirteen coils implanted in an ultrasound prostate phantom.