公开(公告)号：US20070036440A1

公开(公告)日：2007-02-15

申请号：US11582225

申请日：2006-10-17

申请人： Arno Schaepe ,  Maria Athelogou ,  Ursula Benz ,  Christof Krug ,  Gerd Binnig

发明人： Arno Schaepe ,  Maria Athelogou ,  Ursula Benz ,  Christof Krug ,  Gerd Binnig

IPC分类号： G06K9/62 ,  G06F17/30

CPC分类号： G06N5/022 ,  G06K9/00127 ,  G06K9/468 ,  G06K2009/366 ,  Y10S707/99943 ,  Y10S707/99944 ,  Y10S707/99945 ,  Y10S707/99946

摘要： A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

摘要翻译： 公开了一种用于生成分析图像数据的应用的方法，例如从卫星和显微镜图像。 该方法使用图形用户界面将新的处理对象添加到处理对象网络。 处理对象网络包括父处理对象和子处理对象。 用户可以将新的处理对象附加到子处理对象，或者可以将新处理对象作为子处理添加到父处理对象。 用户从图形用户界面的选择列表中选择数据域和算法，并将其添加到新的处理对象。 应用程序使用语义认知网络来处理通过分割图像数据生成的数据对象。 应用程序然后使用新的处理对象来识别图形用户界面上要突出显示的图像的部分。

公开(公告)号：US07467159B2

公开(公告)日：2008-12-16

申请号：US11582225

申请日：2006-10-17

申请人： Arno Schaepe ,  Maria Athelogou ,  Ursula Benz ,  Christof Krug ,  Gerd Binnig

发明人： Arno Schaepe ,  Maria Athelogou ,  Ursula Benz ,  Christof Krug ,  Gerd Binnig

IPC分类号： G06F17/30

CPC分类号： G06N5/022 ,  G06K9/00127 ,  G06K9/468 ,  G06K2009/366 ,  Y10S707/99943 ,  Y10S707/99944 ,  Y10S707/99945 ,  Y10S707/99946

摘要： A method is disclosed for generating an application that analyzes image data, such as from satellite and microscope pictures. The method uses a graphical user interface to add a new processing object to a processing object network. The processing object network includes a parent processing object and a child processing object. A user can append a new processing object to the child processing object or can add the new processing object as a subprocess to the parent processing object. The user selects a data domain and an algorithm from selection lists on the graphical user interface and adds them to the new processing object. The application uses a semantic cognition network to process data objects that are generated by segmenting the image data. The application then uses the new processing object to identify portions of the image that are to be highlighted on the graphical user interface.

摘要翻译： 公开了一种用于生成分析图像数据的应用的方法，例如从卫星和显微镜图像。 该方法使用图形用户界面将新的处理对象添加到处理对象网络。 处理对象网络包括父处理对象和子处理对象。 用户可以将新的处理对象附加到子处理对象，或者可以将新处理对象作为子处理添加到父处理对象。 用户从图形用户界面的选择列表中选择数据域和算法，并将其添加到新的处理对象。 应用程序使用语义认知网络来处理通过分割图像数据生成的数据对象。 应用程序然后使用新的处理对象来识别图形用户界面上要突出显示的图像的部分。

公开(公告)号：US08711149B2

公开(公告)日：2014-04-29

申请号：US13313685

申请日：2011-12-07

申请人： Guenter Schmidt ,  Arno Schaepe ,  Gerd Binnig

发明人： Guenter Schmidt ,  Arno Schaepe ,  Gerd Binnig

IPC分类号： G06T11/20

CPC分类号： G06F19/321 ,  G06F19/00 ,  G06K9/0014 ,  G06T7/0012 ,  G06T11/206 ,  G06T19/00 ,  G06T2200/24 ,  G06T2207/10056 ,  G06T2207/30024 ,  G06T2207/30072 ,  G06T2210/41

摘要： A method of intuitively displaying values obtained from analyzing bio-medical images includes displaying a table of the values in a first pane of a graphical user interface. The table contains a user selectable row that includes a reference value and two numerical values. The reference value refers to an image of a tissue slice. The first numerical value is generated by performing image analysis on the image, and the second numerical value indicates a health state of the tissue. The image is displayed in a second pane of the graphical user interface in response to the user selecting the user selectable row. A graphical plot with a selectable symbol associated with the image is displayed in a third pane. The symbol has a position in the plot defined by the values. Alternatively, in response to the user selecting the selectable symbol, the image is displayed in the second pane.

摘要翻译： 直观地显示从分析生物医学图像获得的值的方法包括在图形用户界面的第一窗格中显示值的表格。 该表包含用户可选行，其中包含一个参考值和两个数值。 参考值是指组织切片的图像。 通过对图像进行图像分析来生成第一数值，第二数值表示组织的健康状态。 响应于用户选择用户可选行，图像显示在图形用户界面的第二窗格中。 具有与图像相关联的可选符号的图形显示在第三窗格中。 符号在由值定义的图中具有位置。 或者，响应于用户选择可选择符号，在第二窗格中显示图像。

公开(公告)号：US08594410B2

公开(公告)日：2013-11-26

申请号：US12930873

申请日：2011-01-18

申请人： Guenter Schmidt ,  Gerd Binnig ,  Ralf Schoenmeyer ,  Arno Schaepe

发明人： Guenter Schmidt ,  Gerd Binnig ,  Ralf Schoenmeyer ,  Arno Schaepe

IPC分类号： G06K9/00 ,  G06K9/62

CPC分类号： G06T7/0014 ,  G01N2800/00 ,  G06K9/6253 ,  G06T7/0012 ,  G06T2207/10116 ,  G06T2207/30004 ,  G06T2207/30061 ,  G06T2207/30068

摘要： An image-based biomarker is generated using image features obtained through object-oriented image analysis of medical images. The values of a first subset of image features are measured and weighted. The weighted values of the image features are summed to calculate the magnitude of a first image-based biomarker. The magnitude of the biomarker for each patient is correlated with a clinical endpoint, such as a survival time, that was observed for the patient whose medical images were analyzed. The correlation is displayed on a graphical user interface as a scatter plot. A second subset of image features is selected that belong to a second image-based biomarker such that the magnitudes of the second image-based biomarker for the patients better correlate with the clinical endpoints observed for those patients. The second biomarker can then be used to predict the clinical endpoint of other patients whose clinical endpoints have not yet been observed.

摘要翻译： 使用通过医学图像的面向对象图像分析获得的图像特征来生成基于图像的生物标志物。 测量和加权图像特征的第一子集的值。 将图像特征的加权值相加以计算第一基于图像的生物标志物的大小。 每个患者的生物标志物的大小与对其医学图像分析的患者观察到的临床终点相关，例如存活时间。 相关性作为散点图显示在图形用户界面上。 选择属于第二基于图像的生物标志物的图像特征的第二子集，使得用于患者的第二基于图像的生物标志物的量级与对于那些患者观察到的临床终点更为相关。 然后可以将第二种生物标志物用于预测尚未观察到其临床终点的其他患者的临床终点。

公开(公告)号：US20120232930A1

公开(公告)日：2012-09-13

申请号：US13417268

申请日：2012-03-11

申请人： Guenter Schmidt ,  Arno Schaepe ,  Thomas Heydler ,  Markus Rinecker ,  Gerd Binnig

发明人： Guenter Schmidt ,  Arno Schaepe ,  Thomas Heydler ,  Markus Rinecker ,  Gerd Binnig

IPC分类号： G06Q50/24

CPC分类号： G06T7/0012 ,  A61B6/502 ,  A61B6/5217 ,  G06F19/321 ,  G06K9/6201 ,  G06Q10/10 ,  G06Q50/22 ,  G06T7/40 ,  G06T2207/10116 ,  G06T2207/30068 ,  G06T2207/30096 ,  G16H50/20 ,  G16H50/70

摘要： A clinical decision support system performs a similarity search to determine the probable outcome of applying on a current patient those clinical actions that were performed on similar patients. The system analyzes stored electronic health records of similar patients so as to recommend diagnostic and therapeutic steps for the current patient. The system receives the health record of the patient, determines which clinical actions were already applied on the patient, generates classifiers associated with potential future clinical actions, generates a success value for each health record of another patient using the classifiers, displays the health record of the other patient having the greatest success value, and indicates a proposed clinical action that is to be applied on the patient. The system also calculates a quality value indicating the probability that a sequence of clinical actions that were applied to a similar patient will be successful if applied to the patient.

摘要翻译： 临床决策支持系统执行相似性搜索以确定对当前患者应用对类似患者进行的临床行为的可能结果。 系统分析类似患者的存储电子健康记录，以便为当前患者推荐诊断和治疗步骤。 该系统接收患者的健康记录，确定哪些临床动作已经应用于患者，产生与潜在的未来临床行为相关联的分类器，使用分类器为另一患者的每个健康记录生成成功值，显示健康记录 其他患者具有最大的成功价值，并且指示将应用于患者的临床行动。 该系统还计算质量值，该质量值指示应用于类似患者的临床行为序列如果应用于患者则成功的概率。

公开(公告)号：US07873223B2

公开(公告)日：2011-01-18

申请号：US11511930

申请日：2006-08-28

申请人： Gerd Binnig ,  Guenter Schmidt ,  Arno Schaepe

发明人： Gerd Binnig ,  Guenter Schmidt ,  Arno Schaepe

IPC分类号： G06K9/62

CPC分类号： G06K9/6253 ,  G06K9/00127 ,  G06K9/0014 ,  G06K9/468 ,  G06K9/6282 ,  G06N5/022

摘要： In a specification mode, a user specifies classes of a class network and process steps of a process hierarchy using a novel scripting language. The classes describe what the user expects to find in digital images. The process hierarchy describes how the digital images are to be analyzed. Each process step includes an algorithm and a domain that specifies the classes on which the algorithm is to operate. A Cognition Program acquires table data that includes pixel values of the digital images, as well as metadata relating to the digital images. In an execution mode, the Cognition Program generates a data network in which pixel values are linked to objects, and objects are categorized as belonging to classes. The process steps, classes and objects are linked to each other in a computer-implemented network structure in a manner that enables the Cognition Program to detect target objects in the digital images.

摘要翻译： 在规范模式中，用户使用新颖的脚本语言来指定类网络的类和处理层次的处理步骤。 这些课程描述了用户期望在数字图像中找到什么。 流程层次描述了数字图像的分析方式。 每个处理步骤包括一个算法和一个域，它指定算法要运行的类。 认知程序获取包括数字图像的像素值的表格数据以及与数字图像有关的元数据。 在执行模式下，认知程序生成数据网络，其中像素值链接到对象，对象被分类为属于类。 过程步骤，类和对象以计算机实现的网络结构彼此链接，使得认知程序能够检测数字图像中的目标对象。

公开(公告)号：US20070122017A1

公开(公告)日：2007-05-31

申请号：US11511930

申请日：2006-08-28

申请人： Gerd Binnig ,  Guenter Schmidt ,  Arno Schaepe

发明人： Gerd Binnig ,  Guenter Schmidt ,  Arno Schaepe

IPC分类号： G06K9/00 ,  G06K9/62

CPC分类号： G06K9/6253 ,  G06K9/00127 ,  G06K9/0014 ,  G06K9/468 ,  G06K9/6282 ,  G06N5/022

摘要： In a specification mode, a user specifies classes of a class network and process steps of a process hierarchy using a novel scripting language. The classes describe what the user expects to find in digital images. The process hierarchy describes how the digital images are to be analyzed. Each process step includes an algorithm and a domain that specifies the classes on which the algorithm is to operate. A Cognition Program acquires table data that includes pixel values of the digital images, as well as metadata relating to the digital images. In an execution mode, the Cognition Program generates a data network in which pixel values are linked to objects, and objects are categorized as belonging to classes. The process steps, classes and objects are linked to each other in a computer-implemented network structure in a manner that enables the Cognition Program to detect target objects in the digital images.

摘要翻译： 在规范模式中，用户使用新颖的脚本语言来指定类网络的类和处理层次的处理步骤。 这些课程描述了用户期望在数字图像中找到什么。 流程层次描述了数字图像的分析方式。 每个处理步骤包括一个算法和一个域，它指定算法要运行的类。 认知程序获取包括数字图像的像素值的表格数据以及与数字图像有关的元数据。 在执行模式下，认知程序生成数据网络，其中像素值链接到对象，对象被分类为属于类。 过程步骤，类和对象以计算机实现的网络结构彼此链接，使得认知程序能够检测数字图像中的目标对象。

公开(公告)号：US09741112B2

公开(公告)日：2017-08-22

申请号：US14850436

申请日：2015-09-10

申请人： Ralf Schoenmeyer ,  Gerd Binnig ,  Guenter Schmidt

发明人： Ralf Schoenmeyer ,  Gerd Binnig ,  Guenter Schmidt

IPC分类号： G06K9/00 ,  G06T7/00 ,  G06F19/00 ,  G06T7/11 ,  G06T7/162 ,  G06T11/20

CPC分类号： G06T7/0012 ,  G06F19/00 ,  G06T7/11 ,  G06T7/162 ,  G06T11/206 ,  G06T2200/04 ,  G06T2207/10056 ,  G06T2207/20016 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30024 ,  G16H50/70

摘要： A method for generating an image-based test improves diagnostic accuracy by iteratively modifying rule sets governing image and data analysis of coregistered image tiles. Digital images of stained tissue slices are divided into tiles, and tiles from different images are coregistered. First image objects are linked to selected pixels of the tiles. First numerical data is generated by measuring the first objects. Each pixel of a heat map aggregates first numerical data from coregistered tiles. Second objects are linked to selected pixels of the heat map. Measuring the second objects generates second numerical data. The method improves how well second numerical data correlates with clinical data of the patient whose tissue is analyzed by modifying the rule sets used to generate the first and second objects and the first and second numerical data. The test is defined by those rule sets that produce the best correlation with the clinical data.

公开(公告)号：US20100265267A1

公开(公告)日：2010-10-21

申请号：US12386380

申请日：2009-04-17

申请人： Arno Schaepe ,  Guenter Schmidt ,  Owen Feehan ,  Gerd Binnig

发明人： Arno Schaepe ,  Guenter Schmidt ,  Owen Feehan ,  Gerd Binnig

IPC分类号： G06K9/62 ,  G06K9/00 ,  G09G5/00 ,  G06F7/00

CPC分类号： G06K9/00637 ,  G06K9/00657 ,  G06K9/469

摘要： An analysis system analyzes digital images using a computer-implemented network structure that includes a process hierarchy, a class network and a data network. The data network includes image layers and object networks. Objects in a first object network are segmented into a first class, and objects in a second object network are segmented into a second class. One process step of the process hierarchy involves generating a third object network by imprinting objects of the first object network into the objects of the second object network such that pixel locations are unlinked from objects of the second object network to the extent that the pixel locations were also linked to objects of the first object network. The imprinting step allows object-oriented processing of digital images to be performed with fewer computations and less memory. Characteristics of an object of the third object network are then determined by measuring the object.

摘要翻译： 分析系统使用包括过程层次，类网络和数据网络的计算机实现的网络结构来分析数字图像。 数据网络包括图像层和对象网络。 第一对象网络中的对象被分割成第一类，并且第二对象网络中的对象被分割成第二类。 过程层级的一个过程步骤包括通过将第一对象网络的对象压印到第二对象网络的对象中来生成第三对象网络，使得像素位置与第二对象网络的对象脱离到像素位置是 也链接到第一对象网络的对象。 压印步骤允许以更少的计算和更少的存储器执行数字图像的面向对象处理。 然后通过测量对象来确定第三对象网络的对象的​​特征。

公开(公告)号：US08989468B2

公开(公告)日：2015-03-24

申请号：US11807096

申请日：2007-05-25

申请人： Gerd Binnig ,  Guenter Schmidt

发明人： Gerd Binnig ,  Guenter Schmidt

IPC分类号： G06K9/00 ,  G06T7/00

CPC分类号： G06T7/0012 ,  G06K9/6268 ,  G06T2200/24 ,  G06T2207/20108 ,  G06T2207/30004

摘要： A system for computer-aided detection uses a computer-implemented network structure to analyze patterns present in digital image slices of a human body and to generate a three-dimensional anatomical model of a patient. The anatomical model is generated by detecting easily identifiable organs first and then using those organs as context objects to detect other organs. A user specifies membership functions that define which objects of the network structure belong to the various classes of human organs specified in a class hierarchy. A membership function of a potentially matching class determines whether a candidate object of the network structure belongs to the potential class based on the relation between a property of the voxels linked to the candidate object and a property of the context object. Some voxel properties used to classify an object are location, brightness and volume. The human organs are then measured to assist in the patient's diagnosis.

摘要翻译： 用于计算机辅助检测的系统使用计算机实现的网络结构来分析存在于人体的数字图像切片中的图案并且生成患者的三维解剖模型。 首先通过检测容易识别的器官，然后使用那些器官作为上下文对象来检测其他器官来产生解剖模型。 用户指定隶属函数，其定义网络结构的哪些对象属于在类层次结构中指定的各种人体器官。 潜在匹配类的隶属函数基于与候选对象链接的体素的属性与上下文对象的属性之间的关系确定网络结构的候选对象是否属于潜在类。 用于分类对象的一些体素属性是位置，亮度和体积。 然后测量人体器官以辅助患者的诊断。