公开(公告)号：US20120327075A1

公开(公告)日：2012-12-27

申请号：US13514713

申请日：2010-11-17

Applicant: Lyubomir Georgiev Zagorchev ,  Elizabeth Anne Morre ,  Matthew A. Garlinghouse ,  Robert M. Roth ,  Thomas W. McAllister ,  Reinhard Kneser ,  Dieter Geller ,  Jochen Peters ,  Juergen Weese ,  Yuechen Qian

Inventor： Lyubomir Georgiev Zagorchev ,  Elizabeth Anne Morre ,  Matthew A. Garlinghouse ,  Robert M. Roth ,  Thomas W. McAllister ,  Reinhard Kneser ,  Dieter Geller ,  Jochen Peters ,  Juergen Weese ,  Yuechen Qian

IPC: G06T7/00

CPC classification number: G06T7/0089 ,  G06T7/0012 ,  G06T7/149 ,  G06T2200/24 ,  G06T2207/10081 ,  G06T2207/30016

Abstract: A system and method for automatic segmentation, performed by selecting a deformable model of an anatomical structure of interest imaged in a volumetric image, the deformable model formed of a plurality of polygons including vertices and edges, displaying the deformable model on a display, detecting a feature point of the anatomical structure of interest corresponding to each of the plurality of polygons and adapting the deformable model by moving each of the vertices toward the corresponding feature points until the deformable model morphs to a boundary of the anatomical structure of interest, forming a segmentation of the anatomical structure of interest.

Abstract translation: 一种用于自动分割的系统和方法，通过选择在体积图像中成像的感兴趣的解剖结构的可变形模型来执行，所述可变形模型由包括顶点和边缘的多个多边形形成，在显示器上显示可变形模型， 感兴趣的解剖结构的特征点对应于多个多边形中的每一个，并且通过将每个顶点朝向对应的特征点移动来适配可变形模型，直到可变形模型变形为感兴趣的解剖结构的边界，形成分割 的感兴趣的解剖结构。

公开(公告)号：US20120066241A1

公开(公告)日：2012-03-15

申请号：US13320956

申请日：2010-05-17

Applicant: Dieter Geller ,  Reinhard Kneser ,  Yuechen Qian

Inventor： Dieter Geller ,  Reinhard Kneser ,  Yuechen Qian

IPC: G06F17/30

CPC classification number: G06F19/3487 ,  G06F19/00 ,  G06F19/321 ,  G06F19/324 ,  G16H15/00

Abstract: As medical imaging becomes more affordable, and the diversity of diagnostic modalities and therapeutic treatments increase, the amount of data being stored increases, and the problem becomes even more critical. One approach to improve retrieval efficiency of images is to employ semantics to establish a defined set of search and classification terms. However, such semantic systems still require the user to make a selection of the most appropriate term or terms to classify a report or image, and the accuracy of the results are thus dependent on the skill and knowledge of the classifier. According to a first aspect of the invention, a retriever is provided for retrieving a medical image having a searchable attribute, the retriever being configured to interface with a semantic database and an image database, and wherein the searchable attribute is determined by segmenting the medical image, using the anatomical model.

Abstract translation: 随着医学成像变得更加实惠，并且诊断模式和治疗方法的多样性增加，存储的数据量增加，并且问题变得更加重要。 提高图像检索效率的一种方法是采用语义来建立一组定义的搜索和分类术语。 然而，这样的语义系统仍然需要用户选择最合适的术语或术语来分类报告或图像，并且结果的准确性因此取决于分类器的技能和知识。 根据本发明的第一方面，提供了一种用于检索具有可搜索属性的医学图像的检索器，所述检索器被配置为与语义数据库和图像数据库进行接口，并且其中通过分割医学图像来确定可搜索属性 ，使用解剖模型。

公开(公告)号：US5745876A

公开(公告)日：1998-04-28

申请号：US642012

申请日：1996-05-02

Applicant: Reinhard Kneser ,  Hermann Ney

Inventor： Reinhard Kneser ,  Hermann Ney

IPC: G10L15/197 ,  G10L5/06

CPC classification number: G10L15/197

Abstract: For the recognition of coherently spoken speech with a large vocabulary, language model values which take into account the probability of word sequences are considered at word transitions. Prior to the recognition, these language model values are derived on the basis of training speech signals. If the amount of training data is kept within sensible limits, not all word sequences will actually occur, so that the language model values for, for example an N-gram language model must be determined from word sequences of N-1 words actually occurring. In accordance with the invention, these reduced word sequences from each different, complete word sequence are counted only once, irrespective of the actual frequency of occurrence of the complete word sequence or only reduced training sequences which occur exactly once in the training data are taken into account.

Abstract translation: 为了识别具有较大词汇量的相干语音，考虑到字序列的概率的语言模型值在词转换中被考虑。 在识别之前，这些语言模型值是基于训练语音信号导出的。 如果训练数据的数量保持在明显的限度内，并不是所有的字序列实际上都会发生，因此，例如N-gram语言模型的语言模型值必须从实际出现的N-1个字的单词序列中确定。 根据本发明，来自每个不同的完整字序列的这些缩减的字序列仅被计数一次，而不考虑完整字序列的实际发生频率，或者仅将训练数据中正好出现一次的训练序列减少 帐户。

公开(公告)号：US09202271B2

公开(公告)日：2015-12-01

申请号：US13642565

申请日：2011-04-18

Applicant: Irina Awechter-Stehle ,  Reinhard Kneser ,  Juergen Weese

Inventor： Irina Awechter-Stehle ,  Reinhard Kneser ,  Juergen Weese

IPC: G06K9/00 ,  G06T7/00 ,  G06T7/60

CPC classification number: G06T7/0012 ,  G06T7/62 ,  G06T2200/04 ,  G06T2207/30101

Abstract: A method and a system for determining a physical property of an object, e.g., a diameter value of an anatomical structure, employs local object context information for determining a local physical property of the object. The context information may be a known or determined cross-sectional shape of the object. In one embodiment, a processor may be configured to provide volumetric image information of the object having a three-dimensional structure; determine the physical property of the object along its three-dimensional structure; determine the object context information of the object; and visualize the object context information and the physical property on a display.

Abstract translation: 用于确定对象的物理属性（例如，解剖结构的直径值）的方法和系统使用用于确定对象的本地物理属性的局部对象上下文信息。 上下文信息可以是对象的已知或确定的横截面形状。 在一个实施例中，处理器可以被配置为提供具有三维结构的对象的体积图像信息; 确定物体沿其三维结构的物理性质; 确定对象的对象上下文信息; 并可视化对象上下文信息和显示器上的物理属性。

公开(公告)号：US09098899B2

公开(公告)日：2015-08-04

申请号：US13699351

申请日：2011-05-18

Applicant: Irina Waechter-Stehle ,  Reinhard Kneser ,  Helko Lehmann ,  Jurgen Weese

Inventor： Irina Waechter-Stehle ,  Reinhard Kneser ,  Helko Lehmann ,  Jurgen Weese

IPC: G06K9/00 ,  G06T7/00 ,  A61B6/12 ,  A61B6/00 ,  A61B8/00 ,  A61B8/08 ,  A61B19/00 ,  A61F2/24 ,  A61F2/82

CPC classification number: G06T7/0012 ,  A61B6/12 ,  A61B6/5247 ,  A61B8/0833 ,  A61B8/0841 ,  A61B8/4416 ,  A61B90/37 ,  A61B90/39 ,  A61B2090/3762 ,  A61B2090/3764 ,  A61B2090/3925 ,  A61B2090/3954 ,  A61B2090/3966 ,  A61B2090/3995 ,  A61F2/2418 ,  A61F2/82 ,  A61F2250/0098 ,  G06T7/73 ,  G06T2207/10088 ,  G06T2207/10116 ,  G06T2207/10132 ,  G06T2207/30052 ,  G06T2207/30101 ,  G06T2207/30204

Abstract: The present invention relates to the determination of the specific orientation of an object. In order to provide enhanced positioning information of an object to a user, a medical imaging system and a method for operating of a medical imaging system are proposed wherein 2D image data (14) of an object is acquired (12) with an imaging system, wherein the object is provided with at least three markers visible in the 2D image; and wherein (16) the markers are detected in the 2D image; and wherein the spatial positioning and rotation angle (20) of the object in relation to the system geometry is identified (18) on behalf of the markers; and wherein an object-indicator (24) is displayed (22) indicating the spatial positioning and rotation angle of the object.

Abstract translation: 本发明涉及确定物体的具体取向。 为了向用户提供对象的增强的定位信息，提出了用成像系统获取物体的2D图像数据（14）的医疗成像系统和医疗成像系统的操作方法， 其中所述对象被提供有在所述2D图像中可见的至少三个标记; 并且其中（16）在2D图像中检测标记; 并且其中所述物体相对于所述系统几何的空间定位和旋转角度（20）代表所述标记被识别（18）; 并且其中显示指示对象的空间定位和旋转角度的对象指示符（24）（22）。

公开(公告)号：US09042629B2

公开(公告)日：2015-05-26

申请号：US12992190

申请日：2009-05-08

Applicant: Yuechen Qian ,  Dieter Geller ,  Reinhard Kneser ,  Merlijn Sevenster ,  Robbert C. Van Ommering ,  Paola K. Tulipano

Inventor： Yuechen Qian ,  Dieter Geller ,  Reinhard Kneser ,  Merlijn Sevenster ,  Robbert C. Van Ommering ,  Paola K. Tulipano

IPC: G06K9/00 ,  G06K9/62 ,  G06T7/00

CPC classification number: G06K9/6267 ,  G06K2209/05 ,  G06T7/0012 ,  G06T7/12 ,  G06T7/149 ,  G06T2207/10072 ,  G06T2207/30041

Abstract: The invention relates to a system (100) for classifying image data on the basis of a model for adapting to an object in the image data, the system comprising a segmentation unit (110) for segmenting the image data by adapting the model to the object in the image data and a classification unit (120) for assigning a class to the image data on the basis of the model adapted to the object in the image data, thereby classifying the image data, wherein the classification unit (120) comprises an attribute unit (122) for computing a value of an attribute of the model on the basis of the model adapted to the object in the image data, and wherein the assigned class is based on the computed value of the attribute. Thus, the system (100) of the invention is capable of classifying the image data without any user input. All inputs required for classifying the image data 10 constitute a model for adapting to an object in the image data. A person skilled in the art will understand however that in some embodiments of the system (100), a limited number of user inputs may be enabled to let the user influence and control the system and the classification process.

Abstract translation: 本发明涉及一种用于基于用于适应图像数据中的对象的模型对图像数据进行分类的系统（100），该系统包括分割单元（110），用于通过将模型适配到对象来分割图像数据 在所述图像数据中，以及分类单元（120），用于基于所述图像数据中适合于所述对象的模型，将类别分配给所述图像数据，从而对所述图像数据进行分类，其中所述分类单元（120）包括属性 单元（122），用于基于适于图像数据中的对象的模型来计算模型的属性的值，并且其中所分配的类基于所计算的属性值。 因此，本发明的系统（100）能够对没有任何用户输入的图像数据进行分类。 分类图像数据10所需的所有输入构成用于适应图像数据中的对象的模型。 然而，本领域技术人员将理解，在系统（100）的一些实施例中，可以使有限数量的用户输入能够使用户影响和控制系统和分类过程。

公开(公告)号：US20130230225A1

公开(公告)日：2013-09-05

申请号：US13884617

申请日：2011-11-09

Applicant: Irina Waechter-Stehle ,  Reinhard Kneser ,  Juergen Weese

Inventor： Irina Waechter-Stehle ,  Reinhard Kneser ,  Juergen Weese

IPC: G06T7/00

CPC classification number: G06T7/0014 ,  A61B6/032 ,  A61B6/463 ,  A61B6/466 ,  A61B6/503 ,  A61B6/504 ,  A61B6/5217 ,  G06K2209/05 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/136 ,  G06T2207/10081 ,  G06T2207/30048 ,  G06T2207/30101

Abstract: A method includes identifying a plurality of different anatomical sub-regions of the cardiovascular system of a subject in image data of the subject based on a subject specific cardiovascular anatomical model, wherein the plurality of different regions corresponds to regions where calcifications occur, searching for and identifying calcifications in the sub-regions based on voxel grey value intensity values of the image data, and generating a signal indicative of one or more regions of voxels of the image data respectively corresponding to sub-regions including identified calcifications. A computing system (118) includes a processor that automatically determines a plurality of different groups of voxels of image data of a subject, wherein each group of voxels corresponds to a different sub-region of the cardiovascular system of the subject and each group of voxels corresponds to a region that includes a calcification identified in the image data.

Abstract translation: 一种方法包括基于主题特异性心血管解剖模型来识别对象的图像数据中的受试者的心血管系统的多个不同解剖子区域，其中所述多个不同区域对应于发生钙化的区域，搜索和 基于图像数据的体素灰度值强度值来识别子区域中的钙化，以及生成指示分别对应于包括识别的钙化的子区域的图像数据的一个或多个体素的区域的信号。 计算系统（118）包括处理器，其自动确定对象的图像数据的多个不同体素组，其中每组体素对应于受试者的心血管系统的不同子区域和每组体素 对应于包括在图像数据中标识的钙化的区域。

公开(公告)号：US20120191720A1

公开(公告)日：2012-07-26

申请号：US13499424

申请日：2010-09-17

Applicant: Merlijn Sevenster ,  Yuechen Qian ,  Robbert Christiaan Van Ommering ,  Reinhard Kneser ,  Dieter Geller

Inventor： Merlijn Sevenster ,  Yuechen Qian ,  Robbert Christiaan Van Ommering ,  Reinhard Kneser ,  Dieter Geller

IPC: G06F17/30

CPC classification number: G06F19/321

Abstract: The invention relates to a system (100) for identifying a document of a plurality of documents, based on a multidimensional image, the system (100) comprising an object unit (110) for identifying an object represented in the multidimensional image, based on a user input indicating a region of the multidimensional image, and further based on a model for modeling the object, determined by segmentation of the indicated region of the multidimensional image; a keyword unit (120) for identifying a keyword of a plurality of keywords, related to the identified object, based on an annotation of the model for modeling the object; and a document unit (130) for identifying the document of the plurality of documents, based on the identified keyword. Thus, the system advantageously facilitates a user's access to documents comprising information of interest based on a viewed multidimensional image. The document may be identified by its name or, preferably, by a link to the document. By following the link, the system may be further adapted to allow the user to retrieve the document stored in a storage comprising the plurality of documents, e.g. download a file comprising the document, and view the document on a display.

Abstract translation: 本发明涉及一种用于基于多维图像来识别多个文档的文档的系统（100），所述系统（100）包括用于基于多维图像识别所述多​​维图像中表示的对象的对象单元（110） 用户输入指示多维图像的区域，并且还基于通过多维图像的指示区域的分割确定的用于建模对象的模型; 用于基于用于建模对象的模型的注释来识别与所识别的对象相关的多个关键字的关键字的关键词单元（120）; 以及用于基于所识别的关键字来识别所述多​​个文档的文档的文档单元（130）。 因此，该系统有利地促进用户基于所观看的多维图像来访问包括感兴趣的信息的文档。 该文件可以由其名称或优选地通过文档的链接来标识。 通过跟随链接，系统可以进一步适于允许用户检索存储在包括多个文档的存储器中的文档，例如， 下载包含文档的文件，并在显示器上查看文档。

公开(公告)号：US20110222747A1

公开(公告)日：2011-09-15

申请号：US12992190

申请日：2009-05-08

Applicant: Yuechen Qian ,  Dieter Geller ,  Reinhard Kneser ,  Merlijn Sevenster ,  Robbert C. Van Ommering ,  Paola K. Tulipano

Inventor： Yuechen Qian ,  Dieter Geller ,  Reinhard Kneser ,  Merlijn Sevenster ,  Robbert C. Van Ommering ,  Paola K. Tulipano

IPC: G06K9/00

CPC classification number: G06K9/6267 ,  G06K2209/05 ,  G06T7/0012 ,  G06T7/12 ,  G06T7/149 ,  G06T2207/10072 ,  G06T2207/30041

Abstract: The invention relates to a system (100) for classifying image data on the basis of a model for adapting to an object in the image data, the system comprising a segmentation unit (110) for segmenting the image data by adapting the model to the object in the image data and a classification unit (120) for assigning a class to the image data on the basis of the model adapted to the object in the image data, thereby classifying the image data, wherein the classification unit (120) comprises an attribute unit (122) for computing a value of an attribute of the model on the basis of the model adapted to the object in the image data, and wherein the assigned class is based on the computed value of the attribute. Thus, the system (100) of the invention is capable of classifying the image data without any user input. All inputs required for classifying the image data 10 constitute a model for adapting to an object in the image data. A person skilled in the art will understand however that in some embodiments of the system (100), a limited number of user inputs may be enabled to let the user influence and control the system and the classification process.

Abstract translation: 本发明涉及一种用于基于用于适应图像数据中的对象的模型对图像数据进行分类的系统（100），所述系统包括分割单元（110），用于通过将模型适配到对象来分割图像数据 在所述图像数据中，以及分类单元（120），用于基于所述图像数据中适合于所述对象的模型，将类别分配给所述图像数据，从而对所述图像数据进行分类，其中所述分类单元（120）包括属性 单元（122），用于基于适于图像数据中的对象的模型来计算模型的属性的值，并且其中所分配的类基于所计算的属性值。 因此，本发明的系统（100）能够对没有任何用户输入的图像数据进行分类。 分类图像数据10所需的所有输入构成用于适应图像数据中的对象的模型。 然而，本领域技术人员将理解，在系统（100）的一些实施例中，可以使有限数量的用户输入能够使用户影响和控制系统和分类过程。