基于B样条的弹性配准在放疗CT图像间配准的应用

目的:应用B样条弹性模型研究肿瘤患者放疗前CT图像与放疗后CT图像之间的弹性配准。方法:利用B样条自由弹性模型(free-form deformations,FFD),以灰度差平方和(Sum of Squared Differences,SSD)为相似性测度函数,通过基于多分辨率的B样条弹性配准方法对同一患者放疗前与放疗后的CT图像进行配准。结果:图像通过高斯滤波处理,应用B样条弹性模型,得到较为理想的弹性配准实验结果。结论:基于B样条的CT与CT图像弹性配准可以较好地建模放疗前与放疗后肿瘤区域的形变,为临床分析肿瘤的变化提供支持。     

基于多对比度磁共振颈动脉图像的配准算法研究

基于在血管壁增强显示方面的强大潜力,近年来多对比度核磁共振成像已成为斑块分析研究的有力工具,但其效能受到多序列图像血管不匹配的影响。为实现多序列图像的准确血管配准,在管腔分割的基础上提出一种由粗到精的两步配准策略:先采用迭代最近点实现多对比度图像中心线的刚性配准,再采用薄板样条实现基于血管边界点的非刚性配准。在第二步配准中,为准确寻找不同序列血管边界的匹配点,创新使用形状上下文描述子对边界点进行筛选,并应用确定性退火技术进行全局优化。采用新型三维多对比度磁共振血管成像序列,对提出算法的有效性进行定量评价。结果表明,配准后不同序列的边界重合度均达到95%以上,平均表面距离0.12 mm,可有效提高配准精度,为后续斑块成分的分析奠定基础。     

血管造影图像序列中冠状动脉的三维运动估计

提出了由两个角度的单面血管造影图像序列估计冠状动脉骨架树三维运动的算法。首先对冠状动脉造影图像序列进行二维预处理和二维运动估计。然后根据冠脉造影系统的透视投影模型得到两幅不同角度的造影图像之间的几何变换关系，以及空间点三维坐标的计算方法。最后，在对整个图像序列进行分析的过程中，将三维运动估计与重建结合起来，得到各骨架点的三维运动向量。采用临床得到的冠状动脉造影图像序列对算法进行了验证，并分析了误差源。     

基于三次样条层间插值的多模态医学图像配准

我们从PET-CT多模态图像序列的特点出发,提出了一种全新的图像配准及融合方法,它采用三次样条插值法对PET-CT图像进行层间插值,然后再利用最大互信息法进行配准,最后应用改进的主成分分析(PCA)法融合PET-CT图像用以增强PET显像效果,从而得到满意的配准以及融合结果。用三次样条插值法进行层间插值并恢复层间缺失图像的信息,弥补了现有配准方法的不足,提高了配准精度,使融合后的图像更加接近实际的物理断层。该方法已经成功应用于三维适形放疗(3D-CRT)系统的开发中。     

肝脏动、静脉相CT图像配准与融合方法研究

目的 研究肝脏CT扫描序列图像轮廓提取、配准与融合问题.方法 采用图像滤波去噪、增强图像边缘及提取图像外轮廓等方法对CT序列图像进行预处理.对肝脏CT扫描序列图像动脉相位期与静脉相位期的图像轮廓进行配准,选取最优配准参数确定不同相位期图像的对应关系,以实现配准.将配准后对应的动、静脉相位期图像融合.结果 融合后的图像展现了同一位置不同相位期肝脏动、静脉的情况.结论 配准、融合后的图像能提供更加丰富的信息,可为医生临床诊断提供参考.     

图像引导HIFU治疗靶区精确定位

靶区精确定位是B超引导HIFU治疗的一个难题。本文利用患者术前采集的CT／MR图像序列与实时B超共同引导进行HIFU治疗靶区精确定位,在没有集成MR设备的HIFU治疗机器上利用了CT／MR图像靶区定位精确的优点。首先在CT／MR图像上进行靶区分割与三维表面重建,再利用三视图多模态医学图像配准技术,将重建的靶区信息映射到超声图像,实现了超声图像上靶区的精确定位。整个引导过程主要包括图像采集、预处理、分割、靶区重建以及多模态图像配准几个部分。这种融合CT／MR图像信息的定位技术有望更好地解决B超引导HIFU治疗中的靶区定位难题。     

基于图像非线性配准的MRI几何失真校正

采用图像非线性配准的方法,对MRI存在的几何失真进行校正,先选取与MRI具有共同解剖结构且基本无几何失真的CT图像,作为配准校正的目标基准图像,将MRI与CT图像进行刚体配准,然后采用人工选点的方法,寻找CT图像和MRI中的对应标记点集,用改进的弹体样条函数进行全局非线性配准.结果表明:弹体样条变换具有较强的非线性校正能力,较好地实现了二维MRI的几何失真校正.我们采用的变换模型有效可行,并可用于三维失真图像的校正.     

基于血管匹配的三维超声与CT图像的配准方法

提出一种基于血管匹配的三维超声与CT图像配准的新方法.首先,基于水平集方法自动分割出CT图像中的血管；其次,由于超声图像中的声影与血管均属于低回声区域,我们结合声影形成的物理原理及图像纹理特性,自动检测出声影区域,以提高配准的鲁棒性；最后,采用进化算法,将CT图像中分割出的血管与超声图像中低回声区域进行匹配.在肝脏体模和临床脾脏数据上进行了实验验证,自动配准的成功率在95％以上,平均目标配准误差在2 mm以内,实验结果验证了本方法的可行性.     

一种基于感兴趣点旋转不变性特征的图像配准新方法

目的:图像配准是图像处理领域重要的研究方向,是图像融合、图像重建和图像分析等研究的基础。在图像配准的主要方法中,基于图像特征的配准方法和基于图像灰度的配准方法各有优缺点,通过结合这两种方法的优点,我们提出了一种基于感兴趣点的旋转不变性特征图像配准的新方法。方法:首先利用Harris角点检测技术,提取模板图像和目标图像的感兴趣点。然后把感兴趣点的旋转不变形特征和灰度值组成图像的特征描述向量,并提出新的代价函数。最后采用分级优化的策略优化代价函数,在配准初期,采用显著的特征点进行配准,以保证配准的速度与鲁棒性,随后通过逐步增加特征点的数量,则保证了配准的精度。结果:为显示本文方法的优越性,实验利用本文方法和基于互信息的B样条方法分别对标准测试图像进行配准,实验结果表明,本文方法较基于互信息的B样条方法在配准精度上有明显提高。结论:本文方法在保持配准鲁棒性的前提下,获得了较高的配准精度。     

冠状动脉的三维运动特征提取

提出一种根据X射线造影图像序列提取冠状动脉血管三维运动特征的方法.首先对由两个角度的造影图像重建得到的三维血管骨架进行运动估计,计算出两个时刻间骨架上各点的三维运动向量.然后结合心脏解剖和运动的先验知识,对血管运动进行定性分析,如位移方向、振幅及运动模式.提取、解释运动信息,并采用符号表达,方便医生进行观察和分析.最后给出了对临床得到的造影图像序列进行实验的结果.     

2D/3D registration of endoscopic ultrasound to CT volume data

This paper describes a computer-aided navigation system using image fusion to support endoscopic interventions such as the accurate collection of biopsy specimens. An endoscope provides the physician with real-time ultrasound (US) and a video image. An image slice that corresponds to the corresponding image from the US scan head is derived from a preoperative computed tomography (CT) or magnetic resonance image volume data set using oblique reformatting and displayed side by side with the US image. The position of the image acquired by the US scan head is determined by a miniaturized electromagnetic tracking system (EMTS) after calibrating the endoscope's scan head. The transformation between the patient coordinate system and the preoperative data set is calculated using a 2D/3D registration. This is achieved by calibrating an intraoperative interventional CT slice with an optical tracking system (OTS) using the same algorithm as for the US calibration. The slice is then used for 2D/3D registration with the coordinate system of the preoperative volume. The fiducial registration error (FRE) for the US calibration was 2.0 mm +/- 0.4 mm; the interventional CT FRE was 0.36 +/- 0.12 mm; and the 2D/3D registration target registration error (TRE) was 1.8 +/- 0.3 mm. The point-to-point registration between the OTS and the EMTS had an FRE of 0.9 +/- 0.4 mm. Finally, we found an overall TRE for the complete system to be 3.9 +/- 0.6 mm.     

CT image registration in sinogram space

Object displacement in a CT scan is generally reflected in CT projection data or sinogram. In this work, the direct relationship between object motion and the change of CT projection data (sinogram) is investigated and this knowledge is applied to create a novel algorithm for sinogram registration. Calculated and experimental results demonstrate that the registration technique works well for registering rigid 2D or 3D motion in parallel and fan beam samplings. Problem and solution for 3D sinogram-based registration of metallic fiducials are also addressed. Since the motion is registered before image reconstruction, the presented algorithm is particularly useful when registering images with metal or truncation artifacts. In addition, this algorithm is valuable for dealing with situations where only limited projection data are available, making it appealing for various applications in image guided radiation therapy.     

Performance studies of four-dimensional cone beam computed tomography

Four-dimensional cone beam computed tomography (4DCBCT) has been proposed to characterize the breathing motion of tumors before radiotherapy treatment. However, when the acquired cone beam projection data are retrospectively gated into several respiratory phases, the available data to reconstruct each phase is under-sampled and thus causes streaking artifacts in the reconstructed images. To solve the under-sampling problem and improve image quality in 4DCBCT, various methods have been developed. This paper presents performance studies of three different 4DCBCT methods based on different reconstruction algorithms. The aims of this paper are to study (1) the relationship between the accuracy of the extracted motion trajectories and the data acquisition time of a 4DCBCT scan and (2) the relationship between the accuracy of the extracted motion trajectories and the number of phase bins used to sort projection data. These aims will be applied to three different 4DCBCT methods: conventional filtered backprojection reconstruction (FBP), FBP with McKinnon-Bates correction (MB) and prior image constrained compressed sensing (PICCS) reconstruction. A hybrid phantom consisting of realistic chest anatomy and a moving elliptical object with known 3D motion trajectories was constructed by superimposing the analytical projection data of the moving object to the simulated projection data from a chest CT volume dataset. CBCT scans with gantry rotation times from 1 to 4 min were simulated, and the generated projection data were sorted into 5, 10 and 20 phase bins before different methods were used to reconstruct 4D images. The motion trajectories of the moving object were extracted using a fast free-form deformable registration algorithm. The root mean square errors (RMSE) of the extracted motion trajectories were evaluated for all simulated cases to quantitatively study the performance. The results demonstrate (1) longer acquisition times result in more accurate motion delineation for each method; (2) ten or more phase bins are necessary in 4DCBCT to ensure sufficient temporal resolution in tumor motion and (3) to achieve the same performance as FBP-4DCBCT with a 4 min data acquisition time, MB-4DCBCT and PICCS-4DCBCT need about 2- and 1 min data acquisition times, respectively.     

Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection

We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DEDR). CT is an established tool for the detection of cardiac calcification. DEDR could be a cost-effective alternative screening tool. In order to utilize CT as the "gold standard" to evaluate the capability of DEDR images for the detection and localization of calcium, we developed an automatic, intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DEDR images. To generate digitally reconstructed radiography (DRR) from the CT volumes, we developed several projection algorithms using the fast shear-warp method. In particular, we created a Gaussian-weighted projection for this application. We used normalized mutual information (NMI) as the similarity measurement. Simulated projection images from CT values were fused with the corresponding DEDR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with a translation difference of less than 0.8 mm and a rotation difference of less than 0.2 degrees. For physical phantom images, the registration accuracy is 0.43 +/- 0.24 mm. Color overlay and 3D visualization of clinical images show that the two images registered well. The NMI values between the DRR and DEDR images improved from 0.21 +/- 0.03 before registration to 0.25 +/- 0.03 after registration. Registration errors measured from anatomic markers decreased from 27.6 +/- 13.6 mm before registration to 2.5 +/- 0.5 mm after registration. Our results show that the automatic 3D-to-2D registration is accurate and robust. This technique can provide a useful tool for correlating DEDR with CT images for screening coronary artery calcification.     

A faster method for 3D/2D medical image registration--a simulation study

3D/2D patient-to-computed-tomography (CT) registration is a method to determine a transformation that maps two coordinate systems by comparing a projection image rendered from CT to a real projection image. Iterative variation of the CT's position between rendering steps finally leads to exact registration. Applications include exact patient positioning in radiation therapy, calibration of surgical robots, and pose estimation in computer-aided surgery. One of the problems associated with 3D/2D registration is the fact that finding a registration includes solving a minimization problem in six degrees of freedom (dof) in motion. This results in considerable time requirements since for each iteration step at least one volume rendering has to be computed. We show that by choosing an appropriate world coordinate system and by applying a 2D/2D registration method in each iteration step, the number of iterations can be grossly reduced from n6 to n5. Here, n is the number of discrete variations around a given coordinate. Depending on the configuration of the optimization algorithm, this reduces the total number of iterations necessary to at least 1/3 of it's original value. The method was implemented and extensively tested on simulated x-ray images of a tibia, a pelvis and a skull base. When using one projective image and a discrete full parameter space search for solving the optimization problem, average accuracy was found to be 1.0 +/- 0.6(degrees) and 4.1 +/- 1.9 (mm) for a registration in six parameters, and 1.0 +/- 0.7(degrees) and 4.2 +/- 1.6 (mm) when using the 5 + 1 dof method described in this paper. Time requirements were reduced by a factor 3.1. We conclude that this hardware-independent optimization of 3D/2D registration is a step towards increasing the acceptance of this promising method for a wide number of clinical applications.     

基于分段B样条形变配准方法的头颈部伪CT生成研究

目的:探讨分段B样条形变配准方法在头颈部伪CT(sCT)生成中的应用,以及对sCT生成精度的影响。方法:收集已经进行调强放射治疗的鼻咽癌患者45例,每例计划均包括头颈部T1加权核磁共振成像(MRI)和CT图像。使用3D Slicer软件对MRI和CT图像分别进行分段B样条形变配准、整体B样条形变配准、分段刚性配准和整体刚性配准4种方法配准,比较配准后的MRI图像和真实CT图像的Dice相似性系数(DSC)值。随机选取其中的30例患者作为训练集,15例患者为测试集,将配准后的MRI和CT图像通过pix2pix网络进行模型训练生成sCT,对生成的sCT和真实CT进行平均绝对误差(MAE)、结构相似性系数(SSIM)和峰值信噪比(PSNR)值的比较,分析通过阈值法分割为不同组织(骨头、软组织、空气和脂肪)的MAE值。结果:配准后的MRI和真实CT图像比较,分段B样条形变配准方法的DSC值最优;使用4种配准方法生成的sCT和真实CT图像进行MAE、SSIM和PSNR值比较,分段配准方法比整体配准方法好,B样条形变配准方法比刚性配准方法好。分段B样条形变配准方法的MAE值为(74.783±9.8...