PROGRESSIVE MODEL-BASED ADAPTATION
    2.
    发明公开
    PROGRESSIVE MODEL-BASED ADAPTATION 有权
    渐进式模块式自适应

    公开(公告)号:EP2143072A2

    公开(公告)日:2010-01-13

    申请号:EP08763047.1

    申请日:2008-04-28

    IPC分类号: G06T7/00

    摘要: The invention relates to an adaptation system for adapting a deformable model to an object of interest in an image data set, the system comprising a propagator for propagating a set of predetermined transformation parameters to the model segments that have not yet been activated for adaptation to the image; an activator for activating at least one model segment from the model segments that have not yet been activated for adaptation to the image; and an adapter for adapting the deformable model by optimizing model energy of the deformable model, said model energy comprising internal energy of the plurality of model segments and external energy of at least the latest activated model segment(s). By enabling propagation of the transformation parameters from the model segments that have been adapted to the image to the model segments that have not been adapted to the image, this invention can improve the robustness and flexibility of the adaptation.

    摘要翻译: 本发明涉及一种用于将可变形模型适应于图像数据集中的感兴趣对象的自适应系统,该系统包括传播器,用于将一组预定变换参数传播到尚未被激活以适应于 图片; 用于激活尚未被激活用于适应图像的模型段的至少一个模型段的激活器; 以及用于通过优化所述可变形模型的模型能量来适配所述可变形模型的适配器,所述模型能量包括所述多个模型段的内部能量和至少最近激活的模型段的外部能量。 通过使来自已经适应于图像的模型段的变换参数能够传播到尚未适应于图像的模型段,本发明可以提高适应性的鲁棒性和灵活性。

    AUTOMATIC TEXT CORRECTION
    4.
    发明公开
    AUTOMATIC TEXT CORRECTION 审中-公开
    自动文本更正

    公开(公告)号:EP1797506A1

    公开(公告)日:2007-06-20

    申请号:EP05786831.7

    申请日:2005-09-28

    IPC分类号: G06F17/22 G10L15/26

    摘要: The present invention provides a method of generating text transformation rules for speech to text transcription systems. The text transformation rules are generated by means of comparing an erroneous text generated by a speech to text transcription system with a correct reference text. Comparison of erroneous and reference text allows to derive a set of text transformation rules that are evaluated by means of a strict application to the training text and successive comparison with the reference text. Evaluation of text transformation rules provides a sufficient approach to determine which of the automatically generated text transformation rules provide an enhancement or degradation of the erroneous text. In this way only those text transformation rules of the set of text transformation rules are selected that guarantee an enhancement of the erroneous text. In this way systematic errors of an automatic speech recognition or natural language process system can be effectively compensated.

    A METHOD OF AND A SYSTEM FOR ADAPTING A GEOMETRIC MODEL USING MULTIPLE PARTIAL TRANSFORMATIONS
    5.
    发明授权
    A METHOD OF AND A SYSTEM FOR ADAPTING A GEOMETRIC MODEL USING MULTIPLE PARTIAL TRANSFORMATIONS 有权
    方法和系统几何模型与几个部分TRANSFORMATIONS适应

    公开(公告)号:EP1929444B1

    公开(公告)日:2011-11-16

    申请号:EP06809355.8

    申请日:2006-09-20

    IPC分类号: G06T7/00

    摘要: The invention relates to a method (100) of adapting a geometric model to an image data comprising determining a first partial transformation for mapping a first part of the geometric model into the image data and a second partial transformation for mapping a second part of the geometric model into the image data. By determining the first partial transformation of the first part of the geometric model and the second partial transformation of the second part of the geometric model, the geometric model can assume more shapes and therefore can be more accurately adapted to an object comprised in the image data.

    摘要翻译: 本发明涉及一种适应几何模型的图像数据包含确定性挖掘的第一部分变换为所述几何模型的第一部分映射到所述图像数据,并且用于映射几何的第二部分的第二部分变换的方法(100) 建模成的图像数据。 通过确定性挖掘几何模型和所述几何模型的第二部分的第二部分变换的所述第一部分的所述第一部分转变,几何模型可以假设更多的形状,因此可更精确地设定angepasst中的图像数据为对象包括 ,

    MODEL-BASED CORONARY CENTERLINE LOCALIZATION
    6.
    发明公开
    MODEL-BASED CORONARY CENTERLINE LOCALIZATION 有权
    MODELLBASIERTE ORTUNG DER KORONAREN ZENTRALLINIE

    公开(公告)号:EP2074585A2

    公开(公告)日:2009-07-01

    申请号:EP07826579.0

    申请日:2007-09-28

    IPC分类号: G06T5/00

    摘要: The invention relates to a system (100) for registering a vessel model with an image data set based on a joined model comprising a reference object model and the vessel model, the system comprising: a placement unit (110) for placing the joined model in a space of the image data set, thereby creating a placed joined model comprising a placed reference object model and a placed vessel model; a computation unit (120) for computing a deformation field based on a landmark displacement field comprising displacements of landmarks of the placed reference object model relative to corresponding landmarks in the image data set; a transformation unit (130) for transforming the placed joined model using the deformation field, thereby creating a transformed joined model comprising a transformed reference object model and a transformed vessel model; and a registration unit (140) for registering the transformed vessel model with the image data set based on modifying the transformed vessel model and optimizing an objective function of the modified transformed vessel model, wherein the objective function comprises a location-prior term based on a localization of the modified transformed vessel model relative to the transformed joined model. Hence, the system is arranged to model a vessel taking into account the localization of a vessel model relative to a reference anatomical structure described by a reference model.

    摘要翻译: 本发明涉及一种用于根据包括参考对象模型和血管模型的联合模型将血管模型注册到图像数据集的系统(100),该系统包括:一个放置单元(110),用于将连接的模型放置在 图像数据集合的空间,从而创建包括放置的参考对象模型和放置的容器模型的放置的连接模型; 计算单元(120),用于基于地标位移场计算变形场,所述地标位移场包括相对于所述图像数据集中的对应界标放置的参考对象模型的界标的位移; 变换单元(130),用于使用变形场变换放置的接合模型,从而创建包括变换的参考对象模型和变换的容器模型的变换的连接模型; 以及注册单元(140),用于基于修改所述经变换的血管模型并优化所述经修改的经转化的血管模型的目标函数,将所述转化的血管模型与所述图像数据集进行登记,其中所述目标函数包括基于 修改的转化血管模型相对于转化的连接模型的定位。 因此,该系统被设置成考虑到血管模型相对于由参考模型描述的参考解剖结构的定位来建模血管。

    TOPIC SPECIFIC MODELS FOR TEXT FORMATTING AND SPEECH RECOGNITION
    7.
    发明公开
    TOPIC SPECIFIC MODELS FOR TEXT FORMATTING AND SPEECH RECOGNITION 有权
    议题的具体型号为文本格式和语音识别

    公开(公告)号:EP1687807A2

    公开(公告)日:2006-08-09

    申请号:EP04799133.6

    申请日:2004-11-12

    摘要: The present invention relates to a method, a computer system and a computer program product for speech recognition and/or text formatting by making use of topic specific statistical models. A text document which may be obtained from a first speech recognition pass is subject to segmentation and to an assignment of topic specific models for each obtained section. Each model of the set of models provides statistic information about language model probabilities, about text processing or formatting rules, as e.g. the interpretation of commands for punctuation, formatting, text highlighting or of ambiguous text portions requiring specific formatting, as well as a specific vocabulary being characteristic for each section of the recognized text. Furthermore, other properties of a speech recognition and/or formatting system (such as e.g. settings for the speaking rate) may be encoded in the statistical models. The models themselves are generated on the basis of annotated training data and/or by manual coding. Based on the assignment of models to sections of text an improved speech recognition and/or text formatting procedure is performed.

    METHOD FOR FACILITATING POST-PROCESSING OF IMAGES USING DEFORMABLE MESHES
    8.
    发明授权
    METHOD FOR FACILITATING POST-PROCESSING OF IMAGES USING DEFORMABLE MESHES 有权
    程序,以方便可变形网络的POST图像

    公开(公告)号:EP1966756B1

    公开(公告)日:2009-07-22

    申请号:EP06842537.0

    申请日:2006-12-14

    IPC分类号: G06T5/00

    摘要: Method and system for facilitating post-processing of images using deformable meshes in which a deformable mesh model of an object such as an organ is extended by attaching information thereon in order to simplify and/or facilitate a desired post-processing task so that the post-processing task effected when the mesh is applied to the same object in an additional image can expeditiously use this information. The information may be attached to the mesh after its creation, for example, upon segmentation of the same object in some training image. The post-processing task can therefore be performed automatically without user interaction upon segmentation of the object in the additional image. Information is encoded on the mesh by enumerating a list of triangles or vertices of the mesh which have to be considered in the subsequent, post-processing task and by optionally providing additional parameters defining the precise post-processing algorithm(s) to be used.

    摘要翻译: 为促进使用可变形网格,其中对象的可变形网格模型图像的后处理方法和系统:诸如器官通过在其上附接信息,以便扩展,以简化和/或促进所期望的后处理任务所以没有交 当网被施加到相同的对象中附加的图像能尽快使用此信息 - 处理任务进行。 该信息可以在创建后附接到网片,例如,当在一些锻炼图像相同的对象的分割。 后处理任务可以被自动THEREFORE无需用户交互在所述对象的分割在附加图像进行。 信息是通过枚举已在随后的后处理任务和由可选地提供附加的参数,定义精确的后处理算法(一个或多个)的使用被认为是网孔的三角形或顶点的列表编码上的网格。

    METHOD FOR FACILITATING POST-PROCESSING OF IMAGES USING DEFORMABLE MESHES
    9.
    发明公开
    METHOD FOR FACILITATING POST-PROCESSING OF IMAGES USING DEFORMABLE MESHES 有权
    程序,以方便可变形网络的POST图像

    公开(公告)号:EP1966756A2

    公开(公告)日:2008-09-10

    申请号:EP06842537.0

    申请日:2006-12-14

    IPC分类号: G06T5/00

    摘要: Method and system for facilitating post-processing of images using deformable meshes in which a deformable mesh model of an object such as an organ is extended by attaching information thereon in order to simplify and/or facilitate a desired post-processing task so that the post-processing task effected when the mesh is applied to the same object in an additional image can expeditiously use this information. The information may be attached to the mesh after its creation, for example, upon segmentation of the same object in some training image. The post-processing task can therefore be performed automatically without user interaction upon segmentation of the object in the additional image. Information is encoded on the mesh by enumerating a list of triangles or vertices of the mesh which have to be considered in the subsequent, post-processing task and by optionally providing additional parameters defining the precise post-processing algorithm(s) to be used.