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公开(公告)号：US20110015520A1
公开(公告)日：2011-01-20
申请号：US12920483
申请日：2009-02-25
CPC分类号： G06F19/321 , A61B6/481 , A61B6/504 , A61B6/507 , G06T7/0012 , G06T2207/10072 , G06T2207/30016 , G06T2207/30101 , G16H40/63 , G16H50/20 , G16H50/50
摘要： A perfusion analysis system includes a perfusion modeller (120) and a user interface (122). The perfusion modeller (120) generates a patient specific perfusion model based on medical imaging perfusion data for the patient, a general perfusion model, and a quantification of one or more identified pathologies of the patient that affect perfusion in the patient. The user interface (122) accepts an input indicative of a modification to the quantification of the one or more identified pathologies. In response, the perfusion modeller (120) updates the patient specific perfusion model based on the medical imaging perfusion data for the patient, the general perfusion model, and the quantification of the one or more identified pathologies of the patient, including the modification thereto.
摘要翻译： 灌注分析系统包括灌注建模器（120）和用户界面（122）。 灌注建模器（120）基于患者的医学成像灌注数据，一般灌注模型和影响患者灌注的患者的一个或多个鉴定的病理学的定量产生患者特异性灌注模型。 用户界面（122）接受指示对所述一个或多个识别的病理学的量化的修改的输入。 作为响应，灌注建模器（120）基于患者的医学成像灌注数据，一般灌注模型和患者的一个或多个鉴定的病理学的定量（包括其修改）来更新患者特异性灌注模型。
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公开(公告)号：US09262590B2
公开(公告)日：2016-02-16
申请号：US13055761
申请日：2009-07-22
CPC分类号： A61N5/1039 , A61B5/055 , A61B6/032 , A61B6/037 , A61N5/103 , G06F19/00 , G06F19/321 , G06F19/3481 , G16H50/50
摘要： A therapy planner is configured to construct a therapy plan based on a planning image segmented into segments delineating features of a subject. A predictive plan adaptation module is configured to adjust the segments to represent a foreseeable change in the subject and to invoke the therapy planner to construct a therapy plan corresponding to the foreseeable change. A data storage stores a plurality of therapy plans generated for a subject by the therapy planner and the predictive plan adaptation module based on at least one planning image of the subject. A therapy plan selector is configured to select one of the plurality of therapy plans for use in a therapy session based on a preparatory image acquired preparatory to the therapy session.
摘要翻译： 治疗计划器被配置为基于划分为描绘对象的特征的段的规划图像来构建治疗计划。 预测计划适应模块被配置为调整分段以表示受试者的可预见的变化，并且调用治疗计划者构建对应于可预见的变化的治疗计划。 数据存储器基于受试者的至少一个规划图像来存储由治疗计划者和预测计划调整模块为受试者生成的多个治疗计划。 治疗计划选择器被配置为基于获得准备治疗会话的准备图像来选择在治疗会话中使用的多个治疗计划中的一个。
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公开(公告)号：US20110130614A1
公开(公告)日：2011-06-02
申请号：US13055761
申请日：2009-07-22
IPC分类号： A61N5/00
CPC分类号： A61N5/1039 , A61B5/055 , A61B6/032 , A61B6/037 , A61N5/103 , G06F19/00 , G06F19/321 , G06F19/3481 , G16H50/50
摘要： A therapy planner (16) is configured to construct a therapy plan based on a planning image segmented into segments delineating features of a subject. A predictive plan adaptation module (20) is configured to adjust the segments to represent a foreseeable change in the subject and to invoke the therapy planner to construct a therapy plan corresponding to the foreseeable change. A data storage (18) stores a plurality of therapy plans generated for a subject by the therapy planner and the predictive plan adaptation module based on at least one planning image of the subject. A therapy plan selector (30) is configured to select one of the plurality of therapy plans for use in a therapy session based on a preparatory image acquired preparatory to the therapy session.
摘要翻译： 治疗计划器（16）被配置为基于划分为描绘对象的特征的段的规划图像来构建治疗计划。 预测计划适应模块（20）被配置为调整所述段以表示所述受试者的可预见的变化，并且调用所述治疗计划者以构建对应于所述可预见的变化的治疗计划。 数据存储器（18）基于所述对象的至少一个规划图像来存储由所述治疗计划器和所述预测计划调整模块为对象生成的针对对象的多个治疗计划。 治疗计划选择器（30）被配置为基于获得准备治疗会话的准备图像来选择用于治疗会话的多个治疗计划中的一个。
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公开(公告)号：US20100246910A1
公开(公告)日：2010-09-30
申请号：US12741838
申请日：2008-11-10
IPC分类号： G06K9/00
CPC分类号： G06T3/0068
摘要： This invention relates to a method and image processing apparatus for automatically correcting mis-orientation of medical images. One or more image processing software modules are used to extract (101) anatomical areas from the medical images. It is determined (103) whether the extracted anatomical areas correspond to reference anatomical areas, but the reference anatomical areas have associated thereto data indicating the orientation of the reference anatomical areas. If the extracted anatomical areas correspond with the reference anatomical areas, the true orientation of the extracted anatomical areas is determined (105) by realigning the medical image until the orientation of the extracted anatomical areas corresponds to the orientation of the reference anatomical areas.
摘要翻译： 本发明涉及一种用于自动校正医学图像的错误取向的方法和图像处理装置。 使用一个或多个图像处理软件模块从医学图像中提取（101）解剖区域。 确定（103）所提取的解剖区域是否对应于参考解剖区域，但是参考解剖区域与其相关联地指示参考解剖区域的取向的数据。 如果提取的解剖区域与参考解剖区域相对应，则通过重新对准医学图像来确定提取的解剖区域的真实取向（105），直到提取的解剖区域的取向对应于参考解剖区域的取向。
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公开(公告)号：US08145012B2
公开(公告)日：2012-03-27
申请号：US10598005
申请日：2005-02-04
申请人： Kirsten Meetz , Heinrich Schulz , Jens Berg , Joerg Sabczynski
发明人： Kirsten Meetz , Heinrich Schulz , Jens Berg , Joerg Sabczynski
CPC分类号： G06T3/4061 , G06T7/30 , G06T2207/10072 , G06T2207/10116 , G06T2207/10132 , G06T2207/30016 , Y10S128/922
摘要： The invention relates to a device and a process, with which images of different imaging methods can be registered, for example preoperatively obtained 3D X-ray images (A) and intra operatively obtained ultrasound images (B). First transformed images (A′,B′) are then generated in a data processing device (10), which are aligned to each other with regard to the peculiarities of each imaging method. Particularly from the three dimensional CT-image (A), can be generated a two dimensional image (A′) which adheres to the characteristic means of representation of an ultrasound system, while shaded areas behind bones and/or gas-filled volumes can be blended out. With a feature-based registration of the transformed images (A′, B′) errors are avoided, which are traced back to artifacts and peculiarities of the respective imaging methods.
摘要翻译： 本发明涉及可以登记不同成像方法的图像的装置和方法，例如，术前获得的3D X射线图像（A）和经操作获得的超声图像（B）。 然后，在数据处理装置（10）中生成第一变换图像（A'，B'），这些数据处理装置相对于每个成像方法的特性彼此对准。 特别是从三维CT图像（A）可以产生一个二维图像（A'），它粘附在超声系统的表征的特征上，而在骨骼和/或充气体积之后的阴影区可以是 混合了 通过改变的图像（A'，B'）的基于特征的注册，避免了错误，这些错误被追溯到各个成像方法的伪影和特征。
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公开(公告)号：US20130021372A1
公开(公告)日：2013-01-24
申请号：US13637674
申请日：2011-03-16
CPC分类号： G06T7/0012 , G06T7/12 , G06T2207/10072 , G06T2207/20101 , G06T2207/20104 , G06T2207/30004
摘要： A method for segmenting image data includes identifying a 2D boundary start position corresponding to tissue of interest in a cross-section of volumetric image data, wherein the start position is identified by a current position of a graphical pointer with respect to the cross-section, generating a preview 2D boundary for the tissue of interest based on the start position, displaying the preview 2D boundary superimposed over the cross-section, and updating the displayed preview 2D boundary if the position of the graphical pointer changes with respect to the cross-section.
摘要翻译： 用于分割图像数据的方法包括：识别在体积图像数据的横截面中对应于感兴趣组织的2D边界开始位置，其中，开始位置由图形指示器相对于横截面的当前位置来识别， 基于开始位置生成针对感兴趣组织的预览2D边界，显示叠加在横截面上的预览2D边界，以及如果图形指针的位置相对于横截面变化则更新显示的预览2D边界 。
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公开(公告)号：US10380735B2
公开(公告)日：2019-08-13
申请号：US13637674
申请日：2011-03-16
摘要： A method for segmenting image data includes identifying a 2D boundary start position corresponding to tissue of interest in a cross-section of volumetric image data, wherein the start position is identified by a current position of a graphical pointer with respect to the cross-section, generating a preview 2D boundary for the tissue of interest based on the start position, displaying the preview 2D boundary superimposed over the cross-section, and updating the displayed preview 2D boundary if the position of the graphical pointer changes with respect to the cross-section.
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公开(公告)号：US20110280461A1
公开(公告)日：2011-11-17
申请号：US13146661
申请日：2010-01-18
IPC分类号： G06K9/00
CPC分类号： G06T7/246 , G06T7/33 , G06T2207/10076 , G06T2207/30061
摘要： A method includes generating a set of group-wise registered images from a time sequence of images based on a region of interest of a subject or object identified in at least one of the images, the image sequence, and a motion model indicative of an estimate of a motion of the subject or object during which the image sequence is acquired.
摘要翻译： 一种方法包括基于图像中的至少一个中识别的对象或对象的感兴趣区域，从图像的时间序列生成一组分组注册图像，图像序列和指示估计的运动模型 获取图像序列的对象或物体的运动。
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公开(公告)号：US20100286995A1
公开(公告)日：2010-11-11
申请号：US12670541
申请日：2008-07-11
申请人： Vladimir Pekar , Torbjoern Vik , Heinrich Schulz , David Jaffray
发明人： Vladimir Pekar , Torbjoern Vik , Heinrich Schulz , David Jaffray
CPC分类号： G06Q50/22 , G06F19/00 , G06T7/12 , G06T7/149 , G06T7/33 , G06T19/00 , G06T2200/24 , G06T2207/20101 , G06T2207/30004 , G06T2210/41
摘要： When modeling anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of predesigned anatomical structure models can be accessed, and model of one or more such structures can be selected and overlaid on an a 3D image of corresponding structure(s) in a clinic image of a patient. A user can click and drag a cursor on the model to deform the model to align with the clinical image. Additionally, a processor (16) can generate a volumetric deformation function using splines, parametric techniques, or the like, and can deform the model to fit the image in real time, in response to user manipulation of the model.
摘要翻译： 当对病人的解剖结构进行建模以进行诊断或治疗计划时，可以访问预先设计的解剖结构模型的图集（26），并且可以选择一个或多个这样的结构的模型并覆盖在对应结构的3D图像上 ）在患者的诊所图像中。 用户可以单击并拖动模型上的光标，使模型变形以与临床图像对齐。 另外，处理器（16）可以使用样条曲线，参数技术等来产生体积变形函数，并且可以响应于模型的用户操纵而实时变形模型以适合图像。
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公开(公告)号：US09730663B2
公开(公告)日：2017-08-15
申请号：US12673779
申请日：2008-08-12
申请人： Thomas Koehler , Holger Schmitt , Heinrich Schulz
发明人： Thomas Koehler , Holger Schmitt , Heinrich Schulz
CPC分类号： A61B6/5258 , G06T7/11 , G06T7/149 , G06T2207/10081 , G06T2207/20012 , G06T2207/30052
摘要： When performing model-based segmentation on a 3D patient image (80), metal artifacts in the patient image (80), caused by metal in the patient's body, are detected, and a metal artifact reduction technique is performed to reduce the artifact(s) by interpolation projection data in the region of the artifact(s). The interpolated data is used to generate an uncertainty map for artifact-affected voxels in the image, and a mesh model (78) is conformed to the image to facilitate segmentation thereof. Internal and external energies applied to push and pull the model (78) are weighted as a function of the uncertainty associated with one or more voxels in the image (80). Iteratively, mathematical representations of the energies and respective weights are solved to describe an updated model shape that more closely aligns to the image (80).
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