计算机辅助手术向远程手术方向的发展

本文对计算机辅助手术(CAS)系统的关键技术:医学图像三维可视化、多模医学图像配准进行了全面的探讨,进一步讨论了在计算机网络中通过共享医学图像的各种分析处理结果,来完成计算机辅助手术向远程手术的转化.对计算机辅助手术向远程手术发展所必须解决的问题;三维医学图像传输环境下的医学图像实时三维可视化、协同分布式并行计算环境、基于Web的交互式可视化进行了设计分析.     

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CUDA的2D-3D医学图像快速配准

医学三维扫描体数据和二维图像配准在临床诊断、手术规划等领域应用广泛,特别是在手术导航时,三维扫描体数据和二维图像的结合既需要保证配准的精度,又要达到手术中即时应用的要求。本文提出一种混合几何和图像密度特征构成的相似度度量函数,对术前CT和术中X线图像进行快速的2D-3D配准,其实现方便、计算量小,同时计算精度可以满足正常的需要。另外,整个计算过程非常适合高度并行的数值计算,通过采用基于CUDA的硬件加速算法,能够达到手术中即时应用的要求。     

基于改进最大互信息法的MR切片图像配准

医学图像配准是医学图像处理分析的关键步骤,是医学图像融合首先要解决的问题。本研究的主要目的是实现帕金森患者深脑部刺激手术前后MR图像的配准。将互距离引入互信息测度,实现手术前后两组MR切片图像的对应匹配,然后将对应的两组MR切片系列重建三维图像,最后用Powell优化算法对重建的三维图像进行配准。通过术前术后MR三维图像的配准,可以定量的分析手术后植入电极和手术前丘脑底核的相对位置关系,从而实现对深脑部刺激手术质量的科学评估。     

集成化三维虚拟手术系统关键问题研究

虚拟手术系统是一种应用图像处理与三维可视化技术的手术仿真软件。外科医生能够应用该系统确定手术位置、模拟手术过程及制订手术计划等。由于ITK具有强大的图像处理能力,而VTK在三维可视化方面具有良好的性能,将VTK与ITK有机地集成起来以解决虚拟手术系统中的图像分割、图像配准与融合、三维重建及虚拟切割等关键技术问题。实验结果证明,这种集成化的三维虚拟手术系统有助于医生观察手术过程,估计手术效果,提高手术的可靠性与质量。     

基于数字血管减影的无框架配准算法的实验研究

我们在无框架立体定位算法的基础上,进行了脑部多模医学图像配准的临床实验研究。实验证明,本配准算法能准确地将数字血管减影(Digital subtraction angiography,DSA)图像中的血管信息融合进计算机体层成像(Computed tomography,CT)的解剖结构中,三维显示后方便医生进行诊断和手术计划,对于计算机辅助外科手术研究具有重要的临床医学价值。     

三维数字化手术设计在青少年特发性脊柱侧凸个性化手术中应用

目的　探讨青少年特发性脊柱侧凸数字化虚拟手术设计系统建立的方法及其在临床应用中的价值。 方法 选取1例青少年特发性脊柱侧凸患者,经16排螺旋CT扫描获取影像数据。采用Mimics 16.01软件对脊柱侧凸影像数据进行三维重建,并对三维重建模型进行数字化三维测量及置钉手术模拟。测量固定内植物的长度、横径及方向,模拟手术经过并在临床应用中使用术前模拟数据。 结果 重建出青少年特发性脊柱侧凸的三维数字化虚拟可视模型,配准虚拟螺钉和椎弓根-肋骨复合体的位置,使虚拟螺钉不穿透椎弓根内侧皮质及椎体前缘,设定完整的手术方案。利用术前规划方案进行手术,手术置钉效果满意,无螺钉穿透椎体前缘皮质和椎管皮质。 结论 验证了特发性脊柱侧凸手术术前三维数字化手术设计并制定手术方案,可以显著提高手术成功率。     

手术导航中人体标志点注册方法和注册精度研究

手术导航IGS(Image guided surgery)指医生在术前获取患者的三维图像模型,术中根据模型引导进行手术治疗的过程.我们介绍了手术导航系统的组成和工作流程,分析了导航系统中,把患者实际体位和模型中虚拟位置精确配准的注册流程和原理,由于注册的精度直接影响着整个导航系统的精度,所以文章着重对注册算法的精度,可行性和鲁棒性进行研究.并结合实际临床导航手术的需求,分析了注册标志点数目和位置等因素对导航精度的影响.     

医学图像三维重建系统的关键技术研究与设计

背景:医学影像三维可视化技术将二维断层图像转化为三维图像,有利于提高医疗规划的准确性,是当今医学领域研究的热点,在诊断医学、手术规划、模拟仿真等领域都有重要的应用。目的:利用二维医学图像序列重建出三维模型的关键技术,对可视化系统进行总体设计。方法:首先研究现有三维重建技术,包括预处理技术,图像分割和配准可视化算法。其次给出了系统体系结构设计图,各模块中应用到各种三维重建关键技术。结果与结论:根据现有关键技术的研究,选用OpenGL作为可视化开发工具,设计了一种基于PC机的三维医学图像可视化系统。     

个体股骨头坏死三维有限元模型的建立与应用

同时基于个体股骨头坏死患者的X-ray、CT和MRI图像,采用图像配准和融合技术对包含坏死股骨头的髋关节进行三维重建,获取具有高度几何相似性的三维有限元网格模型。选择1例中年女性股骨头坏死患者,分别获取X-ray、CT和MRI三套图像,采用Mimics 13.1和Pro/E 5.1软件分别基于这三套数据建立相关三维实体模型,经图像投影转换后,确定图像之间的匹配点,进行二维图像配准,配准后对成功融合的图像进行三维有限元网格模型显示。建立了具有良好几何相似性的髋关节三维有限元网格模型,包括正常皮质骨、松质骨、关节软骨和股骨头坏死区、断裂骨小梁等六部份,较真实地反映了包含坏死股骨头的髋关节的形态特征及毗邻关系,为进一步的生物力学分析和手术模拟提供了较理想的研究平台。     

基于MRI和CT图像配准的颅内电极定位方法

目的应用多模医学图像配准,在颅内电极埋置术后对颅内电极进行精确定位。方法通过对颅内电极埋置前的头颅MRI图像和埋置后头颅CT图像进行配准,利用医学影像配准与分割工具包(ITK),将颅内电极位置准确地定位在MRI图像上,以建立电极位置与大脑解剖结构的联系。结果经过对10组断层图像进行配准定位,差值图像显示匹配程度较好,专家目测融合效果较为精确。在普通PC机上,以笔者所采用的数据为例,设定优化器初始步长为1,松弛因子为0.6,最小步长为0.000 2,最大迭代次数为100,整个电极定位的操作过程时间不超过1 min。结论多模医学图像配准对颅内电极定位较为准确,为医生提供了更加直观和完善的信息。     

An optimised radial basis function algorithm for fast non-rigid registration of medical images

The registration of multi-modal medical image data is important in the fields of image guided surgery and computer aided medical diagnosis. Registration accuracy is of utmost importance in both fields, however in the former, the speed of registration is equally important. In this paper, we present a point-based ‘fast’ non-rigid registration algorithm which exhibits significant speedups as compared to the non-optimised equivalent algorithm. Additionally, we make use of the parallel nature of the graphics processing unit (GPU) of the video adapter card of a standard PC to gain further speedups. The algorithm achieved sub-second performance when tested on the registration of MR with CT image data of size 256³.     

Image-guided,stereotactic perforator flap surgery: a prospective comparison of current techniques and review of the literature

Background  Image-guided stereotaxy is a recent advancement in imaging technology, allowing computer guidance to aid surgical planning and accuracy. Despite the use of multiple techniques for patient registration in several surgical specialities, only fiducial marker registration has been described for use in soft tissue reconstructive surgery. The current study comprises an evaluation of the current techniques available for this purpose. Methods  A cohort of nine consecutive patients planned for elective free flaps were recruited, with the first five patients (four for the abdominal wall and one anterolateral thigh donor site) undergoing fiducial marker registration with a variable number of fiducial markers in order to determine the optimal number of fiducial markers to be used. Four subsequent patients undergoing perforator flap surgery underwent registration using three available registration modalities: fiducial marker registration, surface matching pointer/landmark and surface matching laser registration. Results  For the abdominal wall, registration was not able to be achieved with five fiducial markers, and was successfully achieved in all cases with either six or seven fiducial markers. For the anterolateral thigh, registration was achieved with either nine or ten markers. The four patients who also underwent surface-landmark registration and ‘Z-touch’ laser surface matching registration all failed the registration process. Conclusion  Stereotactic navigation is a useful adjunct to the preoperative imaging of perforator flaps. Fiducial marker registration was able to be achieved in all cases, can be successfully achieved with a low and predictable number of fiducial markers, is highly accurate, and was the only reliable registration process in our experience. W. M. Rozen and A. Buckland are equal first authors. Ethical Approval : Institutional Ethical Approval was obtained through Melbourne Health HREC #2006.231.     

一种基于样本抽样性质的图像配准方法

基于互信息的医学图像配准是当前常用的方法,但互信息的计算量大,对此可采用欠采样技术来减少计算量,但欠采样会降低配准的精度。本文中,我们基于样本抽样均值分布定理,提出了利用多次采样的改进方法,它兼具较高的精度和较快的配准速度。文中的数值计算结果证明了这一点。     

灰度与形状同步匹配的非刚性配准研究

基于灰度的非刚性配准算法一般假设参考图像和浮动图像对应结构之间的灰度保持一致,然而在基于图谱的图像配准应用中,这种假设往往不符合实际。本文在给出一种可以同时校正灰度和形状差异的弹性配准算法的同时,针对该算法不能校正局部微小形变的弱点,提出采用自由项变换的方法进行校正以提高配准精度。配准实验基于20个IBSR真实脑部MRI图像,结果表明配准后图像与参考图像间的互相关系数得到明显提高。实验证明,本文提出的方法不仅能够同时校正形状差异和灰度变化,而且具有较高的配准质量。     

Technical note: a physical phantom for assessment of accuracy of deformable alignment algorithms

The purpose of this study was to investigate the feasibility of a simple deformable phantom as a QA tool for testing and validation of deformable image registration algorithms. A diagnostic thoracic imaging phantom with a deformable foam insert was used in this study. Small plastic markers were distributed through the foam to create a lattice with a measurable deformation as the ground truth data for all comparisons. The foam was compressed in the superior-inferior direction using a one-dimensional drive stage pushing a flat "diaphragm" to create deformations similar to those from inhale and exhale states. Images were acquired at different compressions of the foam and the location of every marker was manually identified on each image volume to establish a known deformation field with a known accuracy. The markers were removed digitally from corresponding images prior to registration. Different image registration algorithms were tested using this method. Repeat measurement of marker positions showed an accuracy of better than 1 mm in identification of the reference marks. Testing the method on several image registration algorithms showed that the system is capable of evaluating errors quantitatively. This phantom is able to quantitatively assess the accuracy of deformable image registration, using a measure of accuracy that is independent of the signals that drive the deformation parameters.     

利用边缘和表面特征实现脑图像CT-MR的自动配准

应用基于CT和MR图像等值特征表面的配准算法对多模医学图像进行了配准研究.在CT、MR图像中提取等值特征表面,进行图像的几何对准,并对结果进行初步评估,同时对该算法的稳健性,搜索最近点策略和插值策略进行了研究.结果表明:这种方法能够达到亚象素级的配准精度,是一种稳健、高精度、全自动的配准方法.     

Optimization of megavoltage CT scan registration settings for brain cancer treatments on tomotherapy

This study aims to determine the settings that provide the optimal clinical accuracy and consistency for the registration of megavoltage CT (MVCT) with planning kilovoltage CT image sets on the Hi-ART tomotherapy system. The systematic offset between the MVCT and the planning kVCT was determined by registration of multiple MVCT scans of a head phantom aligned with the planning isocentre. Residual error vector lengths and components were used to quantify the alignment quality for the phantom shifted by 5 mm in different directions obtained by all 27 possible combinations of MVCT inter-slice spacing, registration techniques and resolution. MVCT scans with normal slices are superior to coarse slices for registration of shifts in the superior-inferior, lateral and anterior-posterior directions. Decreasing the scan length has no detrimental effect on registration accuracy as long as the scan lengths are larger than 24 mm. In the case of bone technique and fine resolution, normal and fine MVCT scan slice spacing options give similar accuracy, so normal mode is preferable due to shorter procedure and less delivered dose required for patient set-up. A superior-inferior field length of 24-30 mm, normal slice spacing, bone technique, and fine resolution is the optimum set of registration settings for MVCT scans of a Rando head phantom acquired with the Hi-ART tomotherapy system, provided the registration shifts are less than 5 mm.     

A material sensitivity study on the accuracy of deformable organ registration using linear biomechanical models

Model-based deformable organ registration techniques using the finite element method (FEM) have recently been investigated intensively and applied to image-guided adaptive radiotherapy (IGART). These techniques assume that human organs are linearly elastic material, and their mechanical properties are predetermined. Unfortunately, the accurate measurement of the tissue material properties is challenging and the properties usually vary between patients. A common issue is therefore the achievable accuracy of the calculation due to the limited access to tissue elastic material constants. In this study, we performed a systematic investigation on this subject based on tissue biomechanics and computer simulations to establish the relationships between achievable registration accuracy and tissue mechanical and organ geometrical properties. Primarily we focused on image registration for three organs: rectal wall, bladder wall, and prostate. The tissue anisotropy due to orientation preference in tissue fiber alignment is captured by using an orthotropic or a transversely isotropic elastic model. First we developed biomechanical models for the rectal wall, bladder wall, and prostate using simplified geometries and investigated the effect of varying material parameters on the resulting organ deformation. Then computer models based on patient image data were constructed, and image registrations were performed. The sensitivity of registration errors was studied by perturbating the tissue material properties from their mean values while fixing the boundary conditions. The simulation results demonstrated that registration error for a subvolume increases as its distance from the boundary increases. Also, a variable associated with material stability was found to be a dominant factor in registration accuracy in the context of material uncertainty. For hollow thin organs such as rectal walls and bladder walls, the registration errors are limited. Given 30% in material uncertainty, the registration error is limited to within 1.3 mm. For a solid organ such as the prostate, the registration errors are much larger. Given 30% in material uncertainty, the registration error can reach 4.5 mm. However, the registration error distribution for prostates shows that most of the subvolumes have a much smaller registration error. A deformable organ registration technique that uses FEM is a good candidate in IGART if the mean material parameters are available.     

Biomechanical Model as a Registration Tool for Image-Guided Neurosurgery: Evaluation Against BSpline Registration

In this paper we evaluate the accuracy of warping of neuro-images using brain deformation predicted by means of a patient-specific biomechanical model against registration using a BSpline-based free form deformation algorithm. Unlike the BSpline algorithm, biomechanics-based registration does not require an intra-operative MR image which is very expensive and cumbersome to acquire. Only sparse intra-operative data on the brain surface is sufficient to compute deformation for the whole brain. In this contribution the deformation fields obtained from both methods are qualitatively compared and overlaps of Canny edges extracted from the images are examined. We define an edge based Hausdorff distance metric to quantitatively evaluate the accuracy of registration for these two algorithms. The qualitative and quantitative evaluations indicate that our biomechanics-based registration algorithm, despite using much less input data, has at least as high registration accuracy as that of the BSpline algorithm.