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。     

利用Contourlet变换进行双源CT图像中的二尖瓣分割

目的 利用双源CT图像对心脏二尖瓣瓣膜进行了增强与分割,为日后进行二尖瓣三维重建和运动分析提供基础。方法 提出了自适应种子填充法和Contourlet小波变换分别用于不同情况下的分割：首先用自适应种子填充法对双源CT胸腔图像进行心脏在造影剂下的区域分割,再用Contourlet小波变换对区域分割后的图像进行二尖瓣的增强和分割。结果 在MATLAB7.0的环境下对双源CT图像成功进行了处理和分割,获取了清晰的心脏二尖瓣图像。结论 本文提出的分割方法对不同情况下的分割非常有效,实验的结论对医生从事二尖瓣瓣膜运动研究和二尖瓣瓣膜外科手术规划提供有益的参考。     

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.     

锥形束CT图像引导乳腺癌放疗中不同配准方法研究

目的：比较锥形束CT(CBCT)图像引导乳腺癌放疗中采用不同配准方法[3D配准（平移）和6D配准（平移+旋转）对配准精度的影响,为选择合理的图像引导方法提供临床依据。方法：回顾性分析18例乳腺癌患者共101次治疗前摆位CBCT图像,将CBCT图像与计划CT图像分别采用3D灰度配准和6D灰度配准方法进行配准,比较和分析两种配准方法的3D平移方向的配准偏差差异并计算其平移差别,进一步统计分析旋转角度偏差与平移差别的相关性并做线性模拟。结果：3D和6D两种配准方法得到不同的平移配准结果,其中在头脚（Y）方向[（-1.47±3.00）mm vs(-0.87±3.27)mm]和前后（Z）方向[（-2.91±4.49）mm vs(-3.41±5.38)mm]的差异存在统计学意义（P<0.001）。旋转角度偏差与平移差别存在相关性,其中ΔX和ΔZ均与Ry呈线性强相关性,其相关系数PCC分别为-0.883和0.795(P<0.001);ΔY与Rx呈线性强负相关性,PCC=-0.722(P<0.001)。根据线性模拟公式计算,当Rx>1°且Ry>2°时,两种配准方法将在各平...     

Tilted plane Feldkamp type reconstruction algorithm for spiral cone beam CT

An approximate image reconstruction method for spiral cone beam computed tomography (CT), called tilted plane Feldkamp type reconstruction algorithm (TPFR), is presented in this paper, which extends Feldkamp cone beam reconstruction algorithm to deal with its inaccuracy and artifact problems caused by large cone angle. This is done by tilting the reconstructing planes to minimize the cone angle and optimally fit the spiral segment of the source. The tilted plane image reconstruction requires reforming the three-dimensional projection data set for the tilted plane and application of Feldkamp algorithm to the reformed data set. Analytical and computational results can show that the image reconstruction performance of the proposed TPFR algorithm is superior to that of the Feldkamp reconstruction algorithm in the image quality, volume coverage speed, maximum achievable pitch value, and slice sensitivity profiles. Moreover, it provides more accurate image reconstruction than the existing two-dimensional reconstruction algorithms.     

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.     

基于Varian锥形束CT影像质量的直线加速器选择策略

目的:定量分析不同锥形束CT（CBCT）影像特点,从而为患者选择最佳设备。方法:利用CatPhan604模体分析Edge、TrueBeam及新旧ix机载CBCT头、胸、盆模式图像。结果:12组图像头、胸、盆CT值最准确的是ix新机器、TrueBeam、Edge,分别为5.69、0.81、6.74 HU;CT值线性最好的是ix旧机器或新机器、Edge、Edge,分别为0.995、0.996、0.997;线性距离误差最小的是ix旧机器、Edge、Edge或TrueBeam或ix旧机器,分别为0.050、0.075、0.100 mm;角度误差最小的是ix旧机器、Edge或TrueBeam、Edge或ix新机器,分别为0.075°、0.050°、0.075°。头、胸、盆高对比度分辨率最好的是ix旧机器、Edge、Edge,分别为7、5、5 LP/cm;均匀性最好的是Edge、Edge、Edge,分别为4.78、20.19、4.63。头、胸、盆噪声最好的是Edge、ix新机器、ix新机器,分别为27.53、8.67、7.33;信噪比最好的是Edge、TrueBeam、ix新机器,分别为83.17、124.39、288.39;对比度噪声比最好的是Edge、ix新机器、ix新机器,分别为11.92、41.42、51.47。低对比度分辨率头部未可见,胸、盆部最好的是Edge或TrueBeam、Edge,分别为6.00、3.75。结论:CBCT系统间差异大,为患者选择加速器时应考虑成像特点,如自适应放疗选择高CT值线性和准确性,立体定向放疗选择低距离和角度误差设备等。     

Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement

The objective of this study was to develop a fully automated two-dimensional (2D)-three-dimensional (3D) registration framework to quantify setup deviations in prostate radiation therapy from cone beam CT (CBCT) data and a single AP radiograph. A kilovoltage CBCT image and kilovoltage AP radiograph of an anthropomorphic phantom of the pelvis were acquired at 14 accurately known positions. The shifts in the phantom position were subsequently estimated by registering digitally reconstructed radiographs (DRRs) from the 3D CBCT scan to the AP radiographs through the correlation of enhanced linear image features mainly representing bony ridges. Linear features were enhanced by filtering the images with "sticks," short line segments which are varied in orientation to achieve the maximum projection value at every pixel in the image. The mean (and standard deviations) of the absolute errors in estimating translations along the three orthogonal axes in millimeters were 0.134 (0.096) AP(out-of-plane), 0.021 (0.023) ML and 0.020 (0.020) SI. The corresponding errors for rotations in degrees were 0.011 (0.009) AP, 0.029 (0.016) ML (out-of-plane), and 0.030 (0.028) SI (out-of-plane). Preliminary results with megavoltage patient data have also been reported. The results suggest that it may be possible to enhance anatomic features that are common to DRRs from a CBCT image and a single AP radiography of the pelvis for use in a completely automated and accurate 2D-3D registration framework for setup verification in prostate radiotherapy. This technique is theoretically applicable to other rigid bony structures such as the cranial vault or skull base and piecewise rigid structures such as the spine.     

一种基于小波变换的配准特征点自动标记算法

以颅脑CT图像为研究对象,提出了一种基于小波变换的自动标记非刚性配准所需对应特征点的算法.这种算法充分考虑了颅脑CT图像的像素点及其临域的纹理特征,通过进行小波变换建立对应于每个像素点的多分辨率小波特征向量,并以小波特征向量间的差异作为判别依据,在目标图像中标记非刚性配准所需的对应特征点.一系列的实验结果表明,这种基于小波变换的算法能够准确地在目标图像中标记出配准所需的对应特征点,可以作为基于特征的非刚性配准对应特征点自动标记的参量之一.     

CT and MR Image Fusion Scheme in Nonsubsampled Contourlet Transform Domain

Fusion of CT and MR images allows simultaneous visualization of details of bony anatomy provided by CT image and details of soft tissue anatomy provided by MR image. This helps the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. This paper aims at designing an effective CT and MR image fusion method. In the proposed method, first source images are decomposed by using nonsubsampled contourlet transform (NSCT) which is a shift-invariant, multiresolution and multidirection image decomposition transform. Maximum entropy of square of the coefficients with in a local window is used for low-frequency sub-band coefficient selection. Maximum weighted sum-modified Laplacian is used for high-frequency sub-bands coefficient selection. Finally fused image is obtained through inverse NSCT. CT and MR images of different cases have been used to test the proposed method and results are compared with those of the other conventional image fusion methods. Both visual analysis and quantitative evaluation of experimental results shows the superiority of proposed method as compared to other methods.     

基于Contourlet变换和PCNN的CT图像椎体解剖轮廓特征提取方法的研究

提出一种新的基于Contourlet变换和脉冲耦合神经网络(PCNN)的医学图像解剖轮廓特征提取算法。首先对原始椎体CT图像进行Contourlet变换,得到能稀疏表示图像边缘以及方向信息的子带和低频子带;然后结合PCNN对低频子带进行边缘轮廓细节提取,最后利用处理后的所有子带系数,通过Contourlet逆变换,提取出图像的边缘轮廓。实验将本算法提取的结果与Canny算子、区域生长法以及结合小波变换和PCNN的算法提取的图像边缘轮廓进行比较,结果表明新算法能够有效的实现医学图像解剖结构轮廓特征的提取。     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.