CN102368972B - 利用患者特异性模型对影像引导进程进行计算机化模拟的系统和方法 - Google Patents

利用患者特异性模型对影像引导进程进行计算机化模拟的系统和方法 Download PDF

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CN102368972B
CN102368972B CN201080012578.9A CN201080012578A CN102368972B CN 102368972 B CN102368972 B CN 102368972B CN 201080012578 A CN201080012578 A CN 201080012578A CN 102368972 B CN102368972 B CN 102368972B
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polygonal mesh
image data
patient
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CN102368972A (zh
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兰·布罗恩施泰因
尼夫·费希尔
奥费克·希隆
埃纳夫·纳默
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00Manipulating 3D models or images for computer graphics
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20Finite element generation, e.g. wire-frame surface description, tesselation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00Manipulating 3D models or images for computer graphics
    • G06T19/20Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00Indexing scheme for image generation or computer graphics
    • G06T2210/41Medical
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2219/00Indexing scheme for manipulating 3D models or images for computer graphics
    • G06T2219/20Indexing scheme for editing of 3D models
    • G06T2219/2021Shape modification

Abstract

本发明的实施方式涉及进行影像引导进程的计算机化模拟的方法。所述方法包括根据医学影像数据产生基于数字影像的解剖结构的模型,根据基于影像的模型和外推数据产生代表解剖结构和未包括在医学影像数据中的邻近解剖区域的扩展模型,显示扩展模型的图解表示,以及利用扩展模型进行影像引导进程的计算机化模拟。

Description

利用患者特异性模型对影像引导进程进行计算机化模拟的系统和方法
背景技术
临床实践正在尽可能地用较小创伤的技术来代替传统的开放式外科进程(程序,方法),然而,其间接地需要基于影像的反馈。在诸如血管导管插入术、血管成形术和支架置入术的影像引导进程中,医生需要识别影像中的解剖结构。如果没有全面的培训,这些进程是难以掌握的,而使用人来进行培训可能是致命的。因此,影像引导进程的模拟系统可以在没有不必要的风险的情况下培训医生,并且也可作为手术前的计划工具或手术后的评估工具。大多数模拟系统基于预定义的解剖结构模型,不是患者特异性的。因此,这样的系统不能在实施手术前准确地计划特定患者的手术,也不能用于手术后的评估。一种更先进的模拟系统是使用患者特异性医学影像数据的患者特异性模拟系统。
附图说明
特别指出并且在说明书的结论部分明确要求保护的为发明的主题。然而本发明既与组织和操作方法有关,又与其对象、特征和优点有关,当阅览附图时,可通过参考以下详细描述最好地理解,其中:
图1示出了根据本发明实施方式的用于模拟影像引导进程的示例性系统;
图2示出了有助于理解本发明实施方式的示例性解剖结构的图解;
图3为说明根据本发明的某些实施方式模拟影像引导进程的方法的流程图;
图4A和图4B示出了根据本发明的实施方式产生的示例性的3D数字模型的图示;
图5为说明根据本发明的一些实施方式,生成影像引导进程的客户特异性模拟扩展模型的示例性方法的流程图;
图6为根据本发明实施方式的扩展模型的示例性3D通用模型的图示;和
图7A和图7B示出了根据本发明的实施方式产生的示例性3D数字模型的图示。
应理解为了简单和明确地说明,图中示出的元件未必是按比例绘制的。例如,可能为了清晰而将某些元件的尺寸相对于其他元件进行放大。此外,在认为适合的情况下,各幅图之间可重复编号以表示相对应的或类似的元件。
具体实施方式
在下面的详细描述中,为了全面理解本发明,提出了许多具体细节。然而,本领域普通技术人员应懂得本发明可在没有这些具体细节的情况下实施。在其他情况下,未详细描述公知的方法、程序、组件、模块、单元和/或流程,以免使本发明含糊不清。
本发明的实施方式涉及患者特异性的影像引导进程的计算机化模拟。该方法可包括根据从对象扫描接收的医学影像数据产生解剖结构的数字模型。该对象可以例如为即将接受影像引导进程的患者。从例如CT系统或任何其他合适的成像系统接收的医学影像数据通常不包括或覆盖要模拟的所关注的整个区域,而是更有限的区域或部分。例如,支架置入术前进行的扫描可通常覆盖紧邻于待治疗区域的区域。如本领域技术人员所理解的,对患者的扫描通常是作为诊断工具进行的,以诊断例如特定解剖区域的病理,因此这样的扫描通常仅覆盖患病、损伤或变化的区域及其紧邻区域。治疗病理的手术或程序可能需要穿过扫描未覆盖的其他解剖区域。医生希望在进行手术之前实践整个进程和/或进行进程后评估。因此,为了能够进行全面的进程模拟,需要其他区域的解剖模型。
根据本发明的实施方式,该方法可包括根据数字模型和代表未包括在医学影像数据中的解剖结构的邻近截面的外推数据来产生扩展模型。扩展模型的图示可显示在监视器上,扩展模型可与其他信息如工具模型一起示出。医生可使用扩展模型进行影像引导进程的计算机化模拟,作为实际手术的预先进程。
医学影像数据可以是患者特异性医学影像,其获得自成像系统如计算机断层扫描(CT)、CT-荧光透视、荧光透视、磁共振成像(MRI)、超声、正电子发射断层扫描(PET)和X-射线。本发明的实施方式可使用医学影像数据作为输入来产生解剖结构、器官和系统的3D或4D模型,并进一步产生包括获得自成像系统而未呈现在医学影像中的区域的扩展模型。
根据影像数据生成的3D模型可以为,例如代表解剖结构三维(3D)表面的多边形网格,结构体积的体素掩码(voxel mask)或面片表面(patchsurface),如2D B-样条等。为了便于说明,根据多边形网格对本发明的实施方式进行描述。然而本领域技术人员应理解,本发明并不限于这样的模型,其他模型也包括在本发明的范围内。
参照图1,图1示出了根据本发明实施方式的用于模拟影像引导进程的示例性系统100。系统100可包括输入单元105、输出单元120、模型生成单元110、模拟单元115和管理单元135。系统100进一步包括存储器130和控制器131。输入单元105可接收医学影像数据并可将该医学影像数据传输至模型生成单元110以产生患者特异的模拟模型。该模型可包括代表未呈现在用作输入数据的医学影像数据中的解剖结构区域的扩展部分。当使用者使用模拟单元115进行模拟作为例如预先进程时,模型图示和模拟过程会显示在输出单元120的监视器(未示出)上。
输入单元105可与成像系统(未示出)如X-射线系统、CT系统、MRI系统和/或超声成像系统相连或接收来自其的医学影像数据。输入单元105可包括鼠标、键盘、触摸屏或触摸板或任意合适的输入设备。可替代地或另外地,输入单元105可包括有线或无线网络接口卡(NIC),以接收来自例如成像系统的数据。根据一些实施方式,输入单元105可与储存医学影像的系统或服务器如影像归档和通信系统(picture archivingcommunication system,PACS)通信,并可从该系统、服务器或应用程序中获得任何相关的影像信息、数据或参数。
模型生成单元110可包括以生成数字模型例如解剖结构如器官脉管系统或体内任何其他重要区域的3D或4D解剖模型及其图示的组件或模块。该模型可根据从成像系统接收的信息,例如,通过输入单元105从CT系统接收的医学影像,通过模型生成单元110生成。模拟单元115可包括用于生成影像引导进程的模拟的组件。根据本发明的实施方式,系统100可进一步包括力反馈装置(未示出),从而当在体内操作物理工具时可模拟对力的感知。
输出单元120可包括与显示屏相连的组件以实现可见的输出或可选地与扬声器或另一音频设备相连以实现可听的输出。输出单元120可包括一个或多个显示器、扬声器和/或任何其他合适的输出装置。输出单元120可与系统100的任何其他组件或单元通信,并由此使该单元能够与外部系统通信。单元105、110和120可以是软件、硬件、固件或它们的任意合适组合或可以包括软件、硬件、固件或它们的任意合适组合。
控制器131可以是任何合适的控制器或处理单元,例如中央处理单元处理器(CPU)。存储器130可以是任何合适的存储组件、装置、芯片或系统,并且可储存可由控制器131执行的应用程序或其他可执行代码。例如,可将执行模型生成和/或模拟的应用程序或模块装载到存储器130中并由控制器131执行。
应认识到,本文描述的系统100为一种示例性的系统。根据本发明的实施方式,可在单一的计算装置上实现系统100,或可替代地在分布式配置中在两个或多个不同的计算装置上实现。例如,模型生成单元110可在第一计算装置上运行并由第一管理单元管理,而模拟单元115可在另一个计算装置上运行并由与该第一管理单元通信的第二管理单元管理。在另一种示例性实施方式中,管理单元135可在计算装置上运行,模型生成单元110可在第二计算装置上运行,模拟单元115可在第三计算装置上运行。
参照图2,其示出了心血管系统的解剖结构的示例性图解,有助于理解本发明的实施方式。当进行影像引导进程模拟,如颈动脉支架术模拟时,使用者可在使用各种导管进行实验的同时在脉管系统中实施导航。通常,出于诊断目的而对患者进行的扫描仅在紧邻损伤处进行。因此,用作输入数据的模拟模型时,这样的扫描可能未包括医生应通过该区域导航而到达损伤处的所有区域。
图2的图解示出了代表用示例性成像系统扫描的区域的顶部区域220和未扫描的底部区域230。因此,医学影像数据仅包括区域220的影像。根据本发明的实施方式,为了进行充分和/或全面的进程模拟,可产生代表扫描区域220和非扫描区域230的用于模拟的扩展模型。根据本发明的实施方式,代表扫描区域的模型部分可由特定对象的医学影像数据生成,并且可见该模型外推至包括未扫描区域的表示。外推可包括从一组预先设计的代表解剖结构的通用模型中选择代表所需的扩展部分的最佳匹配。
例如,在血管成形术如颈动脉支架置入术中,为了到达左脊椎中损伤可能存在的点235,可将导管插入患者身体下部的主动脉中,并引导其通过位于通往左脊椎的路途的点240。因此,在模拟进程中需要包括主动脉的扩展模型。
参照图3,图3为描述了根据本发明一些实施方式的模拟影像引导进程方法的示例性流程图。另外参照图4A和图4B,其示出了根据本发明的实施方式产生的示例性3D数字模型的图示。如框310所示,该方法可包括接收对象的医学影像数据。该医学影像数据从成像或扫描系统接收,如CT或MRI扫描仪。如框315所示,该方法可包括处理所接收的影像数据并根据处理数据生成医学影像中所描绘的解剖结构的模型,该模型是患者特异性的。仅包括在医学影像数据中体现的解剖结构的模型在本文中也被称为基本模型或基于影像的模型。图4A示出了一种示例性的基于影像的模型410,其由部分脉管系统的CT数据处理得到。
根据示例性实施方式,处理可包括将医学影像数据分割。分割涉及将影像区域划分为与不同解剖结构相对应的非重叠区域,以及识别医学影像中所需的解剖结构。其他分割技术,如软分割(soft segmentation)、概率分割或贝叶斯分割(Bayesian segmentation)可实现重叠区域。应认识到,本发明的实施方式对这方面没有限制,可使用任何适用的分割或软分割方法。
可使用全自动算法、具有来自使用者的最小输入的半自动算法、使用者可明确指定所需分割或使用例如CAD工具进行手动分割的定制算法来实现分割过程。分割过程的输出包括将影像数据的一部分作为代表所需解剖结构体积的一组体素(掩码)进行识别。数据的处理进一步包括生成该体积的离散表面,也称为边界表示(boundary-representation,B-rep)。这些表面通常由多边形网格表示,本发明的实施方式对这方面没有限制,其他表示如样条曲面片(spline surface patches)或体素构造表示(实体几何构造法,constructive solid geometry,CSG)或它们的任意混合也同样可能。
处理可进一步包括多边形网格的近似管状截面的中心线的计算,例如血管、肠或结肠。在图4A的示例性基于影像的模型中,中心线代表不同管道的中心线。可通过三次样条(cubic splines)例如Catmul-Rom样条或任何其他合适的数学函数来定义管道中心线。另外地或可替代地,该处理可进一步包括不同管道的半径的计算。
根据某些实施方式,生成医学影像中所描绘的解剖结构的基于影像的模型可包括配准过程。配准(registration)可被定义为将多个数据集校准至单一坐标系中,以使得对应点的空间位置重叠。解剖结构的分割部分可根据代表患者解剖结构的其他模型进行适当定位和旋转。该其他模型可以是本文中所述的通用模型或患者特异性模型。例如,配准模拟血管可包括根据患者的骨骼结构、内脏器官或肺的数字模型对其进行适当定位。配准使得能够呈现出所处理对象的真实影像。配准可进一步实现在保留模拟模型中器官的相对位置、截面、区域或部分的同时,在模拟模型的空间中旋转或浮动或重新定位。
根据某些实施方式,与分割、多边形网格的生成、计算中心线和/或半径有关的程序、任务和/或函数可在分割阶段进行,或在模型生成单元110或模拟单元115启动模拟时进行。本领域技术人员应知晓,虽然通常进行本文中所述内容,但也存在其他实施。例如,模拟单元115可利用一组体素作为输入以生成模型,而无需进行面绘制(surface rendering)和/或中心线或半径的计算和/或配准。应认识到本发明的实施方式不限于示例性方法或所描述的用于生成基于影像的解剖结构的基本模型的系统,在未偏离本发明范围的前提下,也可使用其他方法生成该模型。
再参见图3,根据本发明的实施方式,该方法可包括通过外推医学影像数据中所描绘的基本模型来生成或计算解剖结构的扩展模型(框320)。然后,该方法可包括根据扩展模型进行影像引导进程的患者特异性模拟(框325)。根据本发明的实施方式,对象的医学影像数据中缺失的部分、截面或区域可通过外推根据医学影像数据计算的模型来进行模拟或建模。图4B示出了通过识别图4中的基本模型410的边界并外推该基本模型410并添加外推截面420、421而产生的扩展模型,在图5、图6、图7A和图7B中有详细解释。
参照图5,其为描述了根据本发明的实施方式生成影像引导进程的患者特异性模拟的扩展模型的方法的示例性流程图。另外参照图6、图7A和图7B,它们示出了根据本发明的实施方式产生的典型多边形网格的图示。本发明的实施方式可适用于不同的解剖结构、系统、截面、区域、器官或它们的部分。因此,本文中参照图5所述的方法可适用于生成任何这样的解剖结构的扩展模型。然而,为了简单和清楚,下面的讨论涉及脉管系统的示例性图示说明。应注意本发明的实施方式在这方面没有限制。为了便于说明,根据多边形网格对本发明的实施方式进行了描述。然而本领域技术人员应知晓,本发明并不限于这样的模型,其他模型也包括在本发明的范围内。
根据图5的典型实施方式,输入至外推阶段是指表示为多边形网格的基于影像的模型,其代表基于该影像模型的3D表面,经过适当的配准和旋转,还包括由样条表示的管道中心线。如框510所示,该方法可包括识别一个或多个多边形网格的边界,如图4A的网格410或图7A的网格710。例如,可通过检测仅与一个多边形有关的边缘来检测多边形网格的边界。所检测的边缘可被分为一个或多个连接性组件,其中每个组件与可能需要外推的单一管道的开放性边界相连。
根据本发明的一种示例性实施方式,该方法可包括为每个需要外推的边界选择通用的预先设计的模型以用作扩展截面的模型,其表示为例如多边形网格,如图6的网格610(框515)。通用模型可选自一组预先设计的模型以根据特定参数和规则与开放性边界的边缘最佳匹配。可用多边形网格代表通用模型,以用作对未包括在根据医学影像数据生成的基于影像的模型的区域或截面进行的近似或估计。
所选的通用模型,例如多边形网格,可在数据库、图书馆或任何其他通用网格的存储库中检索。该存储库可存储大量的多边形网格或其他模型,每个模型对应于例如特定解剖位置的特定管道,并具有已知的物理特性如长度和半径。根据本发明的实施方式,可利用预先生成的模型或多边形网格的存储库获得与代表基本的或基于影像模型的多边形网格的开放性边界最接近或最佳匹配的多边形网格。例如,如图7A和图7B所描述,可选择多边形网格610作为基础或起始点,以在边界715处生成截面710的扩展截面720。可基于预定义的分割模型的几何属性组手动或自动进行最佳匹配的选择。另外,可使用手动或自动运行进行选择。根据本发明的实施方式,系统可发送给使用者建议以选择特定的通用模型,然后使用者可手动确认或拒绝建议。
然后,如框525所示,示例性实施方式可包括定位所选的网格使其与边界成一直线。示例性对准方法可利用与预定义的外推网格库有关的中心线,并可且包括在边界附近的分割区域的边缘处计算中心线的切向量。可根据在边缘或所检测边界的点计算这样的切向量。接下来,可定位预定义的或生成的多边形网格中心线上的点。该点可与所计算的模拟器官边界的正切值接近或相同的切向量相关或具有该切向量。使用具有相似切向量的点能够使预定义的多边形网格按照与模拟器官或代表其的多边形网格有关的正确方向定位。
然后,如框530所示,示例性的实施方式可包括将代表基于影像模型的多边形网格的中心线与如图7A所描述的所选的预定义多边形网格的中心线相连接。如此处所述,可根据所计算的正切值进行中心线的连接。可对中心线进行接合、结合或紧密结合(weld),使具有接近、相似或相同正切值的点重叠以确保在3D空间中对基本模型和添加截面进行相似定位或定向。
接下来,如框535所示,示例性实施方式可包括除去多余截面。由于已知由基本多边形网格表示的基本模型的边界的配准,可定义虚框、球体或其他结构化体积以使其包含多边形网格。因此,除去延伸出或在该虚拟体积外的所添加截面的部分,因为其是多余的。可替代地,只有位于该虚拟框或体积内的所选择网格的顶点才能得以保留并如本文所述进行进一步处理。
如框540所示,示例性实施方式可包括缩放所选通用网格的半径以更好地匹配代表基本模型的基本多边形网格的半径。所选择的预定义多边形网格的形状可能不适合或完全匹配其所连接的边界或开放端。此外,虽然如本文所述进行定位或定向,然而代表基本模型的多边形网格和所选的代表扩展截面的多边形网格的中心线在空间中仍然可能是分离的。此外,例如在模拟血管的情况下,预定义的横截面匹配至开放端的外推截面可能不是一个完整的圆形,也不能保证其中心线为精确的圆柱体的数学中心线。因此,可能对中心线周围的每个角度使用不同的缩放因子。
随后,如框545所示,示例性实施方式可能包括将所选的多边形网格的表面与基本多边形网格的表面进行焊接。例如,如图7B所描述,可将基本多边形网格和所选择的预定义多边形网格连接以产生连续表面。可将来自基本多边形网格的边界和来自相应的所选扩展截面的网格的顶点进行连接并用单一顶点表示,同时将多余顶点从模型中除去。对需要扩展的基本模型的每个开放端、边界或边缘重复上述典型方法。
本领域技术人员应理解,可使用多种方法和与基本模型不同或相似的模型来代表扩展解剖结构的预定义的通用模型。根据某些实施方式,代表扩展区域的模型可与基本模型不同。因此,代表外推区域的模型可转换为符合基本模型的另一种格式或表示。然后在所转换表示中的外推区域可与基本模型紧密结合或连接。
可替代地,根据本发明的其他实施方式,多边形网格或代表外推截面的另一合适模型可在进程中(程序性)生成。外推截面或区域的程序性生成可包括识别基本模型的关键属性,如待扩展的边界、相关半径、中心线等。例如,所生成的血管基本模型的中心线可根据第一组规则进行外推。第一组规则的非限定性实例可包括涉及将外推朝着预定方向均匀弯曲的规则。然后,通过例如第二组规则,对模拟血管模型的半径函数进行外推。第二组规则的非限制性实例可包括均匀地将半径从基本模型的识别值朝向预定义长度的预定义值(例如1cm)进行改变,然后在距离顶端的预定义的距离处(例如距离顶端2mm),均匀地将半径改变为零。然后,使用外推中心线和半径函数,生成代表基本模型及其外推的统一多边形网格。
本发明的实施方式可包括物件如计算机或处理器可读的介质,或计算机或处理器的存储介质如存储器、磁盘驱动器或USB快速存储器,其编码、包括或储存指令如计算机可执行指令,当由处理器或控制器执行时,可实施本文所公开的方法。
虽然本发明的实施方式无此方面的限制,但如本文中所使用的,术语“多个”和“复数个”可包括例如“多个”或“两个或更多”。术语“多个”和“复数个”可在整个说明书中使用,以描述两个或多个组件、装置、元件、单元、参数等。
除非明确规定,本文的方法实施方式不限于特定顺序或序列。另外,某些描述的方法实施方式或其元素可能在相同时间点或重叠的时间点进行。如本领域所知,可执行代码段如函数、任务、子任务或程序的执行可称为函数、程序或其他组件的执行。
虽然本发明的实施方式无此方面限制,但利用术语例如“处理”、“计算”、“计算”、“确定”、“建立”、“分析”、“检验”等进行的讨论可能涉及计算机、计算平台、计算系统或其他电子计算设备的运行和/或处理,其将计算机寄存器和/或存储器内的表示为物理(例如电子)量的数据操作和/或转换成计算机寄存器和/或存储器或可储存指令并进行运行和/或处理的其他信息储存介质内的其他类似的表示为物理量的数据。
虽然本文对本发明的某些特征进行了说明和描述,但本领域技术人员将可进行多种修改、替换、更改、及等同替代等。因此,应理解所附权利要求意图覆盖落入本发明实质精神内的所有修改和更改。

Claims (15)

1.一种进行影像引导进程的计算机化模拟的方法,所述方法包括:
根据获自患者的医学影像数据产生所述患者中解剖结构的基于数字影像的模型,所述基于数字影像的模型包括代表所述医学影像数据的第一3D多边形网格;
根据所述基于影像的模型和未包括在所述医学影像数据中的代表解剖结构的邻近截面的数据,产生代表患者中的所述解剖结构和未包括在所述医学影像数据中的邻近解剖区域的扩展模型,其中,产生所述扩展模型包括:
从一组预先设计的通用3D多边形网格中自动选择未包括在所述医学影像数据中的代表解剖结构的第二3D多边形网格,和
定位所述第二3D多边形网格使其与所述第一3D多边形网格的边界成一直线;显示所述扩展模型的图解表示;和
利用所述扩展模型进行影像引导进程的计算机化模拟。
2.根据权利要求1所述的方法,其中,从患者的扫描接收所述医学影像数据,并且所述基于影像的模型为与患者有关的患者特异性模型。
3.根据权利要求1所述的方法,其中,产生所述基于影像的模型包括产生第一3D多边形网格。
4.根据权利要求3所述的方法,其中,产生所述扩展模型包括:
识别所述第一3D多边形网格的边界;
根据空间位置和几何参数,自动选择所述第二3D多边形网格,使得其代表与所述边界最佳匹配的扩展截面;和
将所述第一3D多边形网格的所述边界与所述第二3D多边形网格结合。
5.根据权利要求4所述的方法,其中,所述结合所述边界包括:
计算与所述边界相关的管状截面的中心线;和
将所述第一3D多边形网格的管状截面的所述中心线与所述第二3D多边形网格的中心线相连接。
6.根据权利要求5所述的方法,进一步包括:
除去与多余截面相关的数字数据;和
缩放所述第二3D多边形网格,以使得所述第二3D多边形网格的半径与所述第一3D多边形网格的半径相匹配。
7.根据权利要求1所述的方法,其中,产生所述扩展模型包括:
识别所述基于影像的模型的边界;
识别所述边界的属性;
根据一种或多种所述属性生成在进程中生成的模型作为所述基于影像的模型的扩展,其中所述扩展模型包括所述基于影像的模型和所述在进程中生成的模型。
8.根据权利要求7所述的方法,其中,识别所述边界处的所述属性包括确定所述边界的半径值以及定义与所述边界相关的截面的中心线。
9.根据权利要求1所述的方法,其中,产生所述扩展模型包括:
识别所述基于影像的模型的边界,以第一格式表示所述基于影像的模型;
识别所述边界的属性;和
选择预定义模型作为所述扩展模型,以不同于所述第一格式的第二格式表示所述预定义模型。
10.根据权利要求9所述的方法,进一步包括:
将所述模型的所述第二格式转化为所述第一格式。
11.根据权利要求1所述的方法,其中,产生所述基于影像的模型包括:
分割所述医学影像数据;
识别代表所述解剖结构的所需体积的部分所述影像数据;和
生成所述所需体积的边界表示。
12.根据权利要求1所述的方法,其中,从CT或MRI扫描仪接收所述医学影像数据。
13.根据权利要求1所述的方法,其中,所述解剖结构为血管。
14.一种进行影像引导进程的计算机化模拟的装置,所述装置包括:
模型生成模块,构造为根据获自患者的医学影像数据产生所述患者中解剖结构的基于数字影像的模型,所述基于数字影像的模型包括代表所述医学影像数据的第一3D多边形网格;
以及根据所述基于影像的模型和未包括在所述医学影像数据中的代表解剖结构的邻近截面的数据产生代表所述患者中的所述解剖结构和未包括在所述医学影像数据中的邻近解剖区域的扩展模型,其中,产生所述扩展模型包括:
从一组预先设计的通用3D多边形网格中自动选择未包括在所述医学影像数据中的代表解剖结构的第二3D多边形网格,和
定位所述第二3D多边形网格使其与所述第一3D多边形网格的边界成一直线;
模拟模块,构造为显示所述扩展模型的图解表示,并利用所述扩展模型进行所述影像引导进程的计算机化模拟。
15.根据权利要求14所述的装置,其中,从患者的扫描接收所述医学影像数据,并且所述基于影像的模型为与患者有关的患者特异性模型。
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