多模态图像配准技术在HIFU手术中的应用

在交互式的图像导航热疗手术中 ,需要对病灶目标进行非常精确的实时成像和定位。而现有的超声成像技术很难单独完成这个任务。本研究提出了一种用手术前MRI图像重建的三维图像与手术中的超声图像进行配准的方法 ,对肝部肿瘤热疗手术中的目标进行定位。其配准方法采用的是基于肝部血管和表皮等特征的遗传配准算法。     

基于伪超声和互信息的磁共振与超声图像配准

手术中超声图像与术前磁共振图像的配准在手术导航系统中非常重要。我们利用磁共振和超声成像原理,提出了基于伪超声和互信息,并结合多分辨率技术与Powell优化算法对两种模态图像进行配准的方法,该方法可以有效降低寻优过程中陷入局部极值收敛的概率,提高两种模态图像的配准精度。实验结果表明,我们提出的基于伪超声和互信息的配准方法比目前手术导航系统中普遍采用的标记点方法具有更高的配准精度。     

基于关键点的超声图像与磁共振图像多分辨率离散优化配准方法

脑肿瘤手术规划及术中，术前磁共振（MR）图像与术中超声（US）图像的配准甚为关键。考虑到两种模态图像具有不同密度范围及分辨率，且超声图像存在较多的斑点噪声干扰，采用一种基于局部邻域信息的自相似性上下文（SSC）描述子定义图像之间的相似性测度。将超声图像作为参考，使用三维微分运算提取其中角点作为关键点，并采用密集位移采样离散优化算法实施配准。整个配准过程分为仿射配准和弹性配准两个阶段，在仿射配准阶段，对图像进行多分辨率分解，在弹性配准阶段，采取最小卷积和均值场推理策略对关键点的位移向量进行正则化处理。对22名患者的术前MR和术中US图像进行配准实验，仿射配准后的误差为（1.57±0.30）mm，每对图像配准平均耗时1.36 s；弹性配准后的误差为（1.40±0.28）mm，平均用时1.53 s。实验结果证明本文采用的方法具有良好的配准精度和速度。     

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.     

一种改进的基于互信息的3-D MRI图像配准方法

基于互信息的全局配准算法是近年来图像配准研究的热点之一.该方法具有精度高、鲁棒性强的特点.但目标函数由于插值算法的影响会陷入局部极值,引起误配准.本文实现了一种结合图像滤波预处理进行插值计算的方法,得到更加平滑的目标函数,有效的克服了"插值假像"问题.对标准数据库中的3-D MRI图像进行了刚性配准,实验结果表明该配准方法具有较高的精确度,具有很强的实用性.     

一种基于距离图和分级配准策略的人脑图像非刚体配准方法

目的:基于特征的配准方法中,特征配准结果的好坏决定着最终配准结果的好坏.方法:本文提出了一种基于距离图和分级配准策略的人脑MR图像非刚体配准方法.首先使用C-V模型完成特征的提取工作,并设计了相应的预处理过程,来获得适合进行特征配准的边界点集.接着采用分级配准策略来完成特征配准工作,包括逐条仿射配准和非刚体配准两个子步骤.为了方便计算,距离图被引入到算法过程中,以方便点距的查询.最终的全局配准工作基于特征配准的结果进行,配准问题转化为相应的插值问题进行求解.结果:针对两组初始差异较大的脑部图像进行实验,均可以达到配准要求.结论:实验结果证明,新算法能够适合初始偏差较大配准场合的需求.     

手术导航中空间坐标系配准与注册研究

目的手术导航精度对手术的效果有着至关重要的影响,笔者研究了影响导航精度的因素,包括标志点的选取方法和注册算法。标志点的选取影响配准中两个空间相同目标点的选取,而注册算法影响利用这两组点进行空间配准的精度。方法首先分别阐述了在注册过程中基于点匹配和基于点云的迭代最近点(ICP)匹配点选取方法和注册算法,随后对它们的特点与原理进行分析,比较了其优缺点。提出一种基于点匹配的系统注册方法结合四元数坐标系配准方法,并通过实验验证该方法在将手术空间和图像空间配准时符合手术导航精度要求。同时,分析了这种系统注册方法将来存在的问题和研究方向。结果利用光学导航仪追踪注册模具上的反光球,得到模具内乒乓球的球心坐标,而后在CT图像中获取乒乓球的球心坐标,在Visual Studio中验证两组点的配准,实验结果表明误差在科学可接受范围内。结论这种新的系统注册模具可以用于手术导航注册,结合四元数法精度是符合手术导航精度的。     

基于互信息医学刚性图像配准方法的研究

目的:基于互信息的配准方法是医学图像配准领域的重要方法,具有鲁棒性,精度高等优点。本文探究医学刚性图像配准的有效算法和关键技术。方法:基于互信息配准方法,利用Powell多参数算法和改进的PV插值算法,得到两幅图像之间的最大互信息和最佳配准参数。结果:二维磨牙CT图像配准实验表明,配准速度快,精度提高,验证了插值方法的有效性。结论:方法和算法可提高配准速度,能有效抑制互信息目标函数的局部极值。     

基于GPU的超声成像算法的仿真

超声成像算法的仿真对于成像系统的研究和设计有重要的意义.我们在分析波束形成算法和图形处理器的并行性的基础上,以改进仿真速度为目标,提出了一种新的超声成像算法仿真方案.对基于GPU和基于CPU的仿真方案进行了对比实验,实验所得成像图像完全一致.通过实验证明新的超声成像算法仿真方案是可行的.     

基于灰度和形状的非刚性图像配准算法的研究

提出一种新的灰度和形状信息相结合的全自动同模态医学图像非刚性配准-分割算法,将欧氏距离表示的形状信息融入基于灰度的配准算法中,构造出新的代价函数.该算法在医学图像多目标分割的应用中,能够较好地完成灰度相近、边缘模糊、间距较小的不同结构的分割.对5组真实脑部MRI图像进行分割脑深层灰质结构的实验,结果表明,本算法优于基于灰度信息的图像配准算法.     

Fast treatment plan modification with an over-relaxed Cimmino algorithm

A method to quickly modify a treatment plan in adaptive radiotherapy was proposed and studied. The method is based on a Cimmino-type algorithm in linear programming. The fast convergence speed is achieved by over-relaxing the algorithm relaxation parameter from its sufficient convergence range of (0, 2) to (0, infinity). The algorithm parameters are selected so that the over-relaxed Cimmino (ORC) algorithm can effectively approximate an unconstrained re-optimization process in adaptive radiotherapy. To demonstrate the effectiveness and flexibility of the proposed method in adaptive radiotherapy, two scenarios with different organ motion/deformation of one nasopharyngeal case were presented with comparisons made between this method and the re-optimization method. In both scenarios, the ORC algorithm modified treatment plans have dose distributions that are similar to those given by the re-optimized treatment plans. It takes us using the ORC algorithm to finish a treatment plan modification at least three times faster than the re-optimization procedure compared.     

An optimal algorithm for configuring delivery options of a one-dimensional intensity-modulated beam

The problem of generating delivery options for one-dimensional intensity-modulated beams (1D IMBs) arises in intensity-modulated radiation therapy. In this paper, we present an algorithm with the optimal running time, based on the 'rightmost-preference' method, for generating all distinct delivery options for an arbitrary 1D IMB. The previously best known method for generating delivery options for a 1D IMB with N left leaf positions and N right leaf positions is a 'brute-force' solution, which first generates all N! possible combinations of the left and right leaf positions and then removes combinations that are not physically allowed delivery options. Compared with the brute-force method, our algorithm has several advantages: (1) our algorithm runs in an optimal time that is linearly proportional to the total number of distinct delivery options that it actually produces. Note that for a 1D IMB with multiple peaks, the total number of distinct delivery options in general tends to be considerably smaller than the worst case N!. (2) Our algorithm can be adapted to generating delivery options subject to additional constraints such as the 'minimum leaf separation' constraint. (3) Our algorithm can also be used to generate random subsets of delivery options; this feature is especially useful when the 1D IMBs in question have too many delivery options for a computer to store and process. The key idea of our method is that we impose an order on how left leaf positions should be paired with right leaf positions. Experiments indicated that our rightmost-preference algorithm runs dramatically faster than the brute-force algorithm. This implies that our algorithm can handle 1D IMBs whose sizes are substantially larger than those handled by the brute-force method. Applications of our algorithm in therapeutic techniques such as intensity-modulated arc therapy and 2D modulations are also discussed.     

改进的基于遗传算法稀疏分解的脑CT图像压缩

目的提出一种新型的稀疏分解算法,对脑部CT图像进行压缩。方法本文采用改进的遗传算法（genetic algrithm,GA）与匹配追踪（matching pursuit,MP）算法相结合以实现稀疏分解,对脑部cT图像进行压缩以节约存储空间。针对原有遗传算法计算时间长、匹配率低的不足,本方法优化了迭代次数的选择、竞争、变异等操作。结果利用该算法对脑部CT图像分块压缩,使运算速度、压缩比和信噪比均得到提高。结论通过分析与实验验证,改进的方法压缩比例更大,失真更小,运行时间更短,为脑部CT图像的压缩提供了一种新方法。     

基于混合优化算法的医学图像配准方法

基于互信息的图像配准算法计算复杂度高,配准速度慢。针对这一问题,本文提出一种基于改进遗传算法和Powell算法相结合的医学图像配准方法。首先针对传统遗传算法收敛速度慢、易早熟的缺陷,本文对遗传操作中的交叉运算过程提出了改进策略,并将改进的遗传算法与Powell算法相结合,充分利用遗传算法的全局搜索能力与Powell算法的局部搜索能力。与Powell算法和未改进的遗传算法相比,本文提出的算法极大地缩短了图像配准所用的时间,同时提高了算法的抗噪性。     

脉动流模拟系统血压波形相似度算法研究

目的研究表征血压波形间相似程度的量化指标,并应用到脉动流模拟系统中血压波形的分析。方法在对已有相似度算法进行研究的基础上,结合血压波形自身的特点,提出加权平均算法。该算法将相关系数法和特征参数法相结合,分别从整体和局部特征对波形进行相似性度量,兼具全局匹配和局部比较的优点。结果与夹角余弦法、平均绝对差法和数值型相似系数法相比,加权平均算法更适用于血压波形相似度的分析。结论加权平均算法可以表征不同血压波形之间的差异,比较不同脉动流装置之间的模拟性能,进一步完善后还可以用于其他生理波形的分析。     

A leaf sequencing algorithm to enlarge treatment field length in IMRT

With MLC-based IMRT, the maximum usable field size is often smaller than the maximum field size for conventional treatments. This is due to the constraints of the overtravel distances of MLC leaves and/or jaws. Using a new leaf sequencing algorithm, the usable IMRT field length (perpendicular to the MLC motion) can be mostly made equal to the full length of the MLC field without violating the upper jaw overtravel limit. For any given intensity pattern, a criterion was proposed to assess whether an intensity pattern can be delivered without violation of the jaw position constraints. If the criterion is met, the new algorithm will consider the jaw position constraints during the segmentation for the step and shoot delivery method. The strategy employed by the algorithm is to connect the intensity elements outside the jaw overtravel limits with those inside the jaw overtravel limits. Several methods were used to establish these connections during segmentation by modifying a previously published algorithm (areal algorithm), including changing the intensity level, alternating the leaf-sequencing direction, or limiting the segment field size. The algorithm was tested with 1000 random intensity patterns with dimensions of 21 x 27 cm2, 800 intensity patterns with higher intensity outside the jaw overtravel limit, and three different types of clinical treatment plans that were undeliverable using a segmentation method from a commercial treatment planning system. The new algorithm achieved a success rate of 100% with these test patterns. For the 1,000 random patterns, the new algorithm yields a similar average number of segments of 36.9 +/- 2.9 in comparison to 36.6 +/- 1.3 when using the areal algorithm. For the 800 patterns with higher intensities outside the jaw overtravel limits, the new algorithm results in an increase of 25% in the average number of segments compared to the areal algorithm. However, the areal algorithm fails to create deliverable segments for 90% of these patterns. Using a single isocenter, the new algorithm provides a solution to extend the usable IMRT field length from 21 to 27 cm for IMRT on a commercial linear accelerator using the step and shoot delivery method.     

基于改进光线投射法的冠脉图像三维重建

传统光线投射算法虽然绘制图像时能取得良好的效果，但因为运算速度较慢，限制了其广泛应用。为了在图像三维重建时既能保证质量，又能提高实时交互性，本文提出一种基于改进光线投射算法的冠脉三维重建方法，利用检测原数据点的数据值来简化重采样中三线性插值的复杂性，并结合切比雪夫空体素跳跃法，进一步提高算法的效率。实验结果表明，该算法能够在提高运算速度的同时，保证绘制冠脉三维图像的质量。     

基于蒙特卡洛的医学图像重建体积计算算法GPU加速研究

目的:确定基于蒙特卡洛算法计算体积的精度及提高其速度,为医学图像的应用领域快速提供可靠的数据。 方法:在FonicsPlan计划系统平台上,实现基于蒙特卡洛方法的体积计算,并使用C++AMP对算法做GPU并行加速,然后对体积计算结果在精度和速度上进行比较分析。 结果:与像素累加法、体元累加法相比,蒙特卡洛算法的准确性最高但其算法用时也最长。通过充分利用计算机的显卡计算性能,可将计算速度平均提高50倍。 结论:经GPU加速后的蒙特卡洛算法在计算体积的速度和精度两方面都能满足临床要求,在医学图像处理及临床诊疗具有较高的应用价值。     

A quasiexact reconstruction algorithm for helical CT using a 3-Pi acquisition

Recently, an exact reconstruction method for helical CT was published by A. Katsevich. The algorithm is of the filtered backprojection type and is, therefore, computationally efficient. Moreover, during backprojection, only data are used which correspond to an illumination interval of 180 degrees as seen from the object-point. We propose a new reconstruction method, which is applicable to data obtained with a 3-Pi acquisition [IEEE Trans. Med. Imaging 19, 848-863 (2000)]. The method uses the same filter types as the Katsevich algorithm, but the directions and the number of the filter lines are chosen differently. For the derivation of the new algorithm, we analyze the relationship of the Katsevich method and radon inversion. A certain radon plane can intersect with the backprojection interval related to a 3-Pi acquisition either once, three, or five times. In analogy to the definition of quasiexactness introduced by Kudo et al. for a 1-Pi acquisition, we use the term quasiexactness for algorithms on a 3-Pi acquisition, if radon planes with one or three intersections within the backprojection interval are treated correctly. Using the results on the relationship with radon inversion, we can prove that our algorithm is quasiexact in this sense. We use simulation results in order to demonstrate that the algorithm yields excellent image quality.     

脑Willis环集中参数模型的参数识别算法

目的 探索3种参数识别方法（阻抗模曲线法、阻抗分量法、遗传算法）在脑Willis环11单元集中参数模型参数识别问题求解上的应用。方法 以两侧颈内动脉、椎动脉的流量和压力波形为入口条件,计算正常、两侧椎动脉狭窄情况下模型的参数值,使用Simulink建模对识别算法进行验证,最后对流量加一定噪声验证识别算法的稳定性。结果 正常情况下,阻抗模曲线法获得的近端阻力偏大,阻抗分量法求解的前交通动脉阻力偏大,遗传算法能获得比较合理的模型参数值。两侧椎动脉狭窄情况下,使用阻抗模曲线法能明显得到后循环近端阻力增加的结果,但使用阻抗分量法和遗传算法所得的结果主要是远端阻力有较大增幅。结论 3种方法识别出的参数计算出的压力数据和实际数据仍有差别,考虑为建模误差、源数据误差和计算误差。阻抗模曲线法在区分近端阻力变化上有一定效果,但是某些参数的识别上有较大误差。阻抗分量法能够进行参数识别,但方法不稳定,计算误差较大。遗传算法能获得比较好的近似解,但在区分椎动脉狭窄上存在一定问题。综合阻抗模曲线法和遗传算法可能在未来使用模型进行疾病诊断上发挥比较好的作用。