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.     

X-ray scatter correction algorithm for cone beam CT imaging

Developing and optimizing an x-ray scatter control and reduction technique is one of the major challenges for cone beam computed tomography (CBCT) because CBCT will be much less immune to scatter than fan-beam CT. X-ray scatter reduces image contrast, increases image noise and introduces reconstruction error into CBCT. To reduce scatter interference, a practical algorithm that is based upon the beam stop array technique and image sequence processing has been developed on a flat panel detector-based CBCT prototype scanner. This paper presents a beam stop array-based scatter correction algorithm and the evaluation results through phantom studies. The results indicate that the beam stop array-based scatter correction algorithm is practical and effective to reduce and correct x-ray scatter for a CBCT imaging task.     

Respiratory correlated cone beam CT

A cone beam computed tomography (CBCT) scanner integrated with a linear accelerator is a powerful tool for image guided radiotherapy. Respiratory motion, however, induces artifacts in CBCT, while the respiratory correlated procedures, developed to reduce motion artifacts in axial and helical CT are not suitable for such CBCT scanners. We have developed an alternative respiratory correlated procedure for CBCT and evaluated its performance. This respiratory correlated CBCT procedure consists of retrospective sorting in projection space, yielding subsets of projections that each corresponds to a certain breathing phase. Subsequently, these subsets are reconstructed into a four-dimensional (4D) CBCT dataset. The breathing signal, required for respiratory correlation, was directly extracted from the 2D projection data, removing the need for an additional respiratory monitor system. Due to the reduced number of projections per phase, the contrast-to-noise ratio in a 4D scan reduced by a factor 2.6-3.7 compared to a 3D scan based on all projections. Projection data of a spherical phantom moving with a 3 and 5 s period with and without simulated breathing irregularities were acquired and reconstructed into 3D and 4D CBCT datasets. The positional deviations of the phantoms center of gravity between 4D CBCT and fluoroscopy were small: 0.13 +/- 0.09 mm for the regular motion and 0.39 +/- 0.24 mm for the irregular motion. Motion artifacts, clearly present in the 3D CBCT datasets, were substantially reduced in the 4D datasets, even in the presence of breathing irregularities, such that the shape of the moving structures could be identified more accurately. Moreover, the 4D CBCT dataset provided information on the 3D trajectory of the moving structures, absent in the 3D data. Considerable breathing irregularities, however, substantially reduces the image quality. Data presented for three different lung cancer patients were in line with the results obtained from the phantom study. In conclusion, we have successfully implemented a respiratory correlated CBCT procedure yielding a 4D dataset. With respiratory correlated CBCT on a linear accelerator, the mean position, trajectory, and shape of a moving tumor can be verified just prior to treatment. Such verification reduces respiration induced geometrical uncertainties, enabling safe delivery of 4D radiotherapy such as gated radiotherapy with small margins.     

Feature-based rectal contour propagation from planning CT to cone beam CT

The purpose of this work is to develop a novel feature-based registration strategy to automatically map the rectal contours from planning computed tomography (CT) (pCT) to cone beam CT (CBCT). The rectal contours were manually outlined on the pCT. A narrow band with the outlined contour as its interior surface was then constructed, so that we can exclude the volume inside the rectum in the registration process. The corresponding contour in the CBCT was found by using a feature-based registration algorithm, which consists of two steps: (1) automatically searching for control points in the pCT and CBCT based on the features of the surrounding tissue and matching the homologous control points using the scale invariance feature transformation; and (2) using the control points for a thin plate spline transformation to warp the narrow band and mapping the corresponding contours from pCT to CBCT. The proposed contour propagation technique is applied to digital phantoms and clinical cases and, in all cases, the contour mapping results are found to be clinically acceptable. For clinical cases, the method yielded satisfactory results even when there were significant rectal content changes between the pCT and CBCT scans. As a consequence, the accordance between the rectal volumes after deformable registration and the manually segmented rectum was found to be more than 90%. The proposed technique provides a powerful tool for adaptive radiotherapy of prostate, rectal, and gynecological cancers in the future.     

An energy-based beam hardening model in tomography

As a consequence of the polychromatic x-ray source, used in micro-computer tomography (microCT) and in medical CT, the attenuation is no longer a linear function of absorber thickness. If this nonlinear beam hardening effect is not compensated, the reconstructed images will be corrupted by cupping artefacts. In this paper, a bimodal energy model for the detected energy spectrum is presented, which can be used for reduction of artefacts caused by beam hardening in well-specified conditions. Based on the combination of the spectrum of the source and the detector efficiency, the assumption is made that there are two dominant energies which can describe the system. The validity of the proposed model is examined by fitting the model to the experimental datapoints obtained on a microtomograph for different materials and source voltages.     

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.     

Helical cone beam CT with an asymmetrical detector

If a multislice or other area detector is shifted to one side to cover a larger field of view, then the data are truncated on one side. We propose a method to restore the missing data in helical cone-beam acquisitions that uses measured data on the longer side of the asymmetric detector array. The method is based on the idea of complementary rays, which is well known in fan beam geometry; in this paper we extend this concept to the cone-beam case. Different cases of complementary data coverage and dependence on the helical pitch are considered. The proposed method is used in our prototype 16-row CT scanner with an asymmetric detector and a 700 mm field of view. For evaluation we used scanned body phantom data and computer-simulated data. To simulate asymmetric truncation, the full, symmetric datasets were truncated by dropping either 22.5% or 45% from one side of the detector. Reconstructed images from the prototype scanner with the asymmetrical detector show excellent image quality in the extended field of view. The proposed method allows flexible helical pitch selection and can be used with overscan, short-scan, and super-short-scan reconstructions.     

Noise simulation in cone beam CT imaging with parallel computing

We developed a computer noise simulation model for cone beam computed tomography imaging using a general purpose PC cluster. This model uses a mono-energetic x-ray approximation and allows us to investigate three primary performance components, specifically quantum noise, detector blurring and additive system noise. A parallel random number generator based on the Weyl sequence was implemented in the noise simulation and a visualization technique was accordingly developed to validate the quality of the parallel random number generator. In our computer simulation model, three-dimensional (3D) phantoms were mathematically modelled and used to create 450 analytical projections, which were then sampled into digital image data. Quantum noise was simulated and added to the analytical projection image data, which were then filtered to incorporate flat panel detector blurring. Additive system noise was generated and added to form the final projection images. The Feldkamp algorithm was implemented and used to reconstruct the 3D images of the phantoms. A 24 dual-Xeon PC cluster was used to compute the projections and reconstructed images in parallel with each CPU processing 10 projection views for a total of 450 views. Based on this computer simulation system, simulated cone beam CT images were generated for various phantoms and technique settings. Noise power spectra for the flat panel x-ray detector and reconstructed images were then computed to characterize the noise properties. As an example among the potential applications of our noise simulation model, we showed that images of low contrast objects can be produced and used for image quality evaluation.     

基于Contourlet变换的CT和锥形束CT图像配准算法

目的提出一种基于Contourlet变换,用于放射治疗定位的CT与锥形束CT（cone beam CT,CBCT）图像配准的方法。方法利用Contourlet变换多尺度多方向的分辨特性,将待配准图像进行Contourlet变换分解,分解后的高频方向子带合成梯度图像,采用归一化互信息作为相似性测度,把梯度图像与低频方向子带以加权函数结合,进行临床医学图像的刚性配准,有效弥补了互信息配准中缺少空间信息的不足。结果通过已知空间变换参数图像的配准结果验证了算法的准确性。配准后lO幅图像变换参数的误差极小,且均方根误差接近于0。结论该图像配准算法精确度高,并具有很好的鲁棒性,有助于提高图像引导放射治疗（image guid edradiation therapy,IGRT）中解剖组织结构和靶区的定位精度。     

Image registration algorithm in CT and cone beam CT based on Contourlet transform

目的提出一种基于Contourlet变换,用于放射治疗定位的CT与锥形束CT(cone beam CT,CBCT)图像配准的方法.方法 利用Contourlet变换多尺度多方向的分辨特性,将待配准图像进行Contourlet变换分解,分解后的高频方向子带合成梯度图像,采用归一化互信息作为相似性测度,把梯度图像与低频方向子带以加权函数结合,进行临床医学图像的刚性配准,有效弥补了互信息配准中缺少空间信息的不足.结果 通过已知空间变换参数图像的配准结果验证了算法的准确性.配准后10幅图像变换参数的误差极小,且均方根误差接近于0.结论 该图像配准算法精确度高,并具有很好的鲁棒性,有助于提高图像引导放射治疗(image guided radiation therapy,IGRT)中解剖组织结构和靶区的定位精度.     

A geometric calibration method for cone beam CT systems

Cone beam CT systems are being deployed in large numbers for small animal imaging, dental imaging, and other specialty applications. A new high-precision method for cone beam CT system calibration is presented in this paper. It uses multiple projection images acquired from rotating point-like objects (metal ball bearings) and the angle information generated from the rotating gantry system is also used. It is assumed that the whole system has a mechanically stable rotation center and that the detector does not have severe out-of-plane rotation (<2 degrees). Simple geometrical relationships between the orbital paths of individual BBs and five system parameters were derived. Computer simulations were employed to validate the accuracy of this method in the presence of noise. Equal or higher accuracy was achieved compared with previous methods. This method was implemented for the geometrical calibration of both a micro CT scanner and a breast CT scanner. The reconstructed tomographic images demonstrated that the proposed method is robust and easy to implement with high precision.     

A general framework and review of scatter correction methods in cone beam CT. Part 2: scatter estimation approaches

The main components of scatter correction procedures are scatter estimation and a scatter compensation algorithm. This paper completes a previous paper where a general framework for scatter compensation was presented under the prerequisite that a scatter estimation method is already available. In the current paper, the authors give a systematic review of the variety of scatter estimation approaches. Scatter estimation methods are based on measurements, mathematical-physical models, or combinations of both. For completeness they present an overview of measurement-based methods, but the main topic is the theoretically more demanding models, as analytical, Monte-Carlo, and hybrid models. Further classifications are 3D image-based and 2D projection-based approaches. The authors present a system-theoretic framework, which allows to proceed top-down from a general 3D formulation, by successive approximations, to efficient 2D approaches. A widely useful method is the beam-scatter-kernel superposition approach. Together with the review of standard methods, the authors discuss their limitations and how to take into account the issues of object dependency, spatial variance, deformation of scatter kernels, external and internal absorbers. Open questions for further investigations are indicated. Finally, the authors refer on some special issues and applications, such as bow-tie filter, offset detector, truncated data, and dual-source CT.     

Adaptive temporal resolution optimization in helical cardiac cone beam CT reconstruction

Cone beam computed tomography scanners in combination with heart rate adaptive reconstruction schemes have the potential to enable cardiac volumetric computed tomography (CT) imaging for a larger number of patients and applications. In this publication, an adaptive scheme for the automatic and patient-specific reconstruction optimization is introduced to improve the temporal resolution and image quality. The optimization method permits the automatic determination of the required amount of gated helical cone beam projection data for the reconstruction volume. It furthermore allows one to optimize subvolume reconstruction yielding an increased temporal resolution. In addition, methods for the assessment of the temporal resolution are given which enable a quantitative documentation of the reconstruction improvements. Results are presented for patient data sets acquired in low pitch helical mode using a 16-slice cone beam CT system with parallel ECG recording.     

Effect of scattered radiation on image noise in cone beam CT

Cone beam CT has a capability for the 3-dimensional imaging of large volumes with isotropic resolution, and has a potentiality for 4-dimensional imaging (dynamic volume imaging), because cone beam CT acquires data of a large volume with one rotation of an x-ray tube-detector pair. However, one of the potential drawbacks of cone beam CT is a larger amount of scattered x-rays, which may enhance the noise in reconstructed images, and thus affect the low-contrast detectablity. Our aim in this work was to estimate the scatter fractions and effects of scatter on image noise, and to seek methods of improving image quality in cone beam CT. First we derived a relationship between the noise in a reconstructed image and in an x-ray intensity measurement. Then we estimated the scatter to primary ratios in x-ray measurements using a Monte-Carlo simulation. From these we estimated the image noise under relevant clinical conditions. The results showed that the scattered radiation made a substantial contribution to the image noise. However, focused collimators could improve it by decreasing the scattered radiation drastically while keeping the primary radiation at nearly the same level. A conventional grid also improved the image noise, though the improvement was less than that of focused collimators.     

Spatial resolution properties in cone beam CT: a simulation study

This work is intended to investigate the spatial resolution properties in cone beam CT by estimating the point spread functions (PSFs) in the reconstructed 3D images through simulation. The point objects were modeled as 3D delta functions. Their projections onto the detector plane were analytically derived and blurred with 2D PSFs estimated and used to represent the detector and focal spot blurring effects. The 2D PSF for detector blurring was computed from the line spread function measured for a typical a-Si/CsI flat panel detector used for general radiography. The focal spot blurring effect was simulated for an x-ray source with a nominal focal spot size of 0.6 mm and 1.33 x magnification at the rotating center. Projection images were computed and sampled with an interval significantly smaller than the detector pixel size to avoid aliasing. Images were reconstructed using the Feldkamp algorithm with the five different filter functions. Reconstructed PSFs were plotted and analyzed to investigate the effects of detector blurring alone, focal spot blurring alone, or a combination of the two on the PSFs and their variations with the radial distance and z-level. Effects of binning and reconstruction filters were also studied. Our results show that the PSFs due to detector blurring are largely symmetric and vary little with the locations of the point objects. With focal spot blurring only or added to detector blurring, the PSFs along the rotation axis were largely symmetric but became increasingly asymmetric as the point objects were moved away from the rotation axis. The PSFs were found to become wider in the axial (anode to cathode) direction as the objects were moved toward the cathode side. The 3D PSFs may be approximated by an ellipsoid with three different axial lengths. They were found to point upright along the rotating axis but tilt toward the rotating axis as the point object was moved away from the axis.     

基于DenseCUT网络由头部锥形束CT图像生成合成CT图像

提出一种由头部锥形束CT(CBCT)图像生成合成CT(sCT)图像的无监督深度学习网络,并与循环生成对抗（CycleGAN）网络及对比非配对转换（CUT）网络进行比较。本研究共获取56例脑部肿瘤患者的计划CT(pCT)和CBCT数据（其中49例用于训练,7例用于测试）,分别使用CycleGAN网络、CUT网络以及本研究提出的密集对比非配对转换（DenseCUT）网络由CBCT图像生成sCT。DenseCUT网络有两点创新之处：将CUT网络与密集块网络结合;在损失函数中加入结构相似性。与pCT-CBCT相比,pCT-sCT(DenseCUT网络)的HU值平均绝对误差从34.38 HU降低到17.75 HU,峰值信噪比从26.19 dB提升到29.83 dB,结构相似性从0.78提升到0.87。本文方法可在不改变解剖结构的情况下从CBCT图像中生成高质量的sCT图像,同时降低图像伪影,使CBCT应用于剂量计算和自适应放疗计划成为可能。     

Linac-integrated 4D cone beam CT: first experimental results

A new online imaging approach, linac-integrated cone beam CT (CBCT), has been developed over the past few years. It has the advantage that a patient can be examined in their treatment position directly before or during a radiotherapy treatment. Unfortunately, respiratory organ motion, one of the largest intrafractional organ motions, often leads to artefacts in the reconstructed 3D images. One way to take this into account is to register the breathing phase during image acquisition for a phase-correlated image reconstruction. Therefore, the main focus of this work is to present a system which has the potential to investigate the correlation between internal (movement of the diaphragm) and external (data of a respiratory gating system) information about breathing phase and amplitude using an inline CBCT scanner. This also includes a feasibility study about using the acquired information for a respiratory-correlated 4D CBCT reconstruction. First, a moving lung phantom was used to develop and to specify the required methods which are based on an image reconstruction using only projections belonging to a certain moving phase. For that purpose, the corresponding phase has to be detected for each projection. In the case of the phantom, an electrical signal allows one to track the movement in real time. The number of projections available for the image reconstruction depends on the breathing phase and the size of the position range from which projections should be used for the reconstruction. The narrower this range is, the better the inner structures can be located, but also the noise of the images increases due to the limited number of projections. This correlation has also been analysed. In a second step, the methods were clinically applied using data sets of patients with lung tumours. In this case, the breathing phase was detected by an external gating system (AZ-733V, Anzai Medical Co.) based on a pressure sensor attached to the patient's abdominal region with a fixation belt. The comparison of the reconstructed 4D CBCT images and the corresponding 4D CT images used for the treatment planning provides the required information for the calculation of possible setup errors. So, a repositioning of the patient is feasible even though the patient moves due to respiration. In addition to the external signal, the position of the diaphragm in the cranial-caudal direction could be extracted from each projection. Both independent sources of information show a very good agreement of the phase and even the amplitude of the movement and the external signal respectively. This suggests the usability of such a system for a gated dose delivery approach. However, more studies involving patients with different incidences have to be carried out to confirm these first results.     

前列腺癌靶区位移影响因素分析

目的 深层次探究直肠肌肉张力、腹内压和盆腔骨骼3个客观因素对前列腺癌放疗前锥形束CT校准数据影响,得到影响前列腺靶区运动主要因素,为优化放疗计划设计和提高图像引导精度提供参考.方法 依据试验纳排标准,筛选符合条件的10名前列腺癌患者,接受每周两次随机治疗前锥形束CT扫描,获取前列腺靶区校准数据.扫描之后,分别采用剪切波超声弹性成像技术量化患者直肠肌肉张力影响,采用气囊测压表测量膀胱内压间接量化腹内压影响,采用误差均方根量化盆腔骨骼影响.回归分析3个因素与锥形束CT校准数据之间关系.结果 所有患者左右、前后、头脚方向上锥形束CT校准结果分别为:0.513 mm±0.072 mm、1.369 mm±0.162 mm、1.335 mm±0.271 mm;杨氏模量值:8.965 kPa±1.391 kPa、10.211 kPa±1.544 kPa、3.926 kPa±0.693 kPa,腹内压(未分方向):4.844 mmHg±1.347 mmHg(1 mmHg=133.3 Pa),误差均方根:0.020 mm±0.011 mm、0.069 mm±0.049 mm、0.052 mm±0.029 mm;前后方向上直肠肌肉张力(R=0.895)和腹内压(R=0.523)均同锥形束CT校准数据存在统计学意义相关性,头脚方向上腹内压(R=0.717)存在统计学意义相关性.结论 前后方向上直肠肌肉张力和头脚方向上腹内压是造成前列腺癌靶区位移主要因素,结果对优化放疗计划设计和提高图像引导精度具有重要意义,并为未来降低靶区位移提供了方法学指导.