公开(公告)号：US09740912B2

公开(公告)日：2017-08-22

申请号：US13330900

申请日：2011-12-20

申请人： Ralf Schoenmeyer ,  Gerd Binnig ,  Guenter Schmidt ,  Maria Athelogou ,  Peter Ellenberg

发明人： Ralf Schoenmeyer ,  Gerd Binnig ,  Guenter Schmidt ,  Maria Athelogou ,  Peter Ellenberg

IPC分类号： G06K9/00 ,  G06K9/34 ,  G06T17/00 ,  G09G5/00 ,  G06T7/33

CPC分类号： G06K9/0014 ,  G06T7/33 ,  G06T2207/10056 ,  G06T2207/30024

摘要： A method for co-registering images of tissue slices stained with different biomarkers displays a first digital image of a first tissue slice on a graphical user interface such that an area of the first image is enclosed by a frame. Then a portion of a second image of a second tissue slice is displayed such that the area of the first image enclosed by the frame is co-registered with the displayed portion of the second image. The displayed portion of the second image has the shape of the frame. The tissue slices are both z slices of a tissue sample taken at corresponding positions in the x and y dimensions. The displayed portion of the second image is shifted in the x and y dimensions to coincide with the area of the first image that is enclosed by the frame as the user shifts the first image under the frame.

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：US20130108139A1

公开(公告)日：2013-05-02

申请号：US13282450

申请日：2011-10-26

申请人： Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

发明人： Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

IPC分类号： G06K9/34

CPC分类号： G06T7/0012 ,  G06K9/0014 ,  G06K9/34 ,  G06K9/4652 ,  G06K9/6215 ,  G06T7/11 ,  G06T7/155 ,  G06T7/187 ,  G06T7/90 ,  G06T2207/10024 ,  G06T2207/10056 ,  G06T2207/30024

摘要： A method for determining whether a test biomarker is a stain for a type of cell component, such as membrane or nucleus, involves performing various segmentation processes on an image of tissue stained with the test biomarker. One segmentation process searches for a first cell component type, and another segmentation process searches for a second cell component type by segmenting only stained pixels. The test biomarker is identified as a stain for each component type if the process identifies the component based only on stained pixels. Whether the test biomarker is a membrane stain or nucleus stain is displayed on a graphical user interface. In addition, the method identifies stained pixels corresponding to a second cell component using pixels determined to correspond to a first cell component. An expression profile for the test biomarker is then displayed that indicates the proportion of stained pixels in each type of cell component.

公开(公告)号：US20130016886A1

公开(公告)日：2013-01-17

申请号：US13546182

申请日：2012-07-11

申请人： Ralf Schoenmeyer ,  Peter Ellenberg ,  Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

发明人： Ralf Schoenmeyer ,  Peter Ellenberg ,  Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

IPC分类号： G06K9/50

CPC分类号： G06T7/0012 ,  G06T11/206 ,  G06T2207/10061 ,  G06T2207/20016 ,  G06T2207/20021 ,  G06T2207/20221

摘要： High-resolution digital images of adjacent slices of a tissue sample are acquired, and tiles are defined in the images. Values associated with image objects detected in each tile are calculated. The tiles in adjacent images are co-registered. A first hyperspectral image is generated using a first image, and a second hyperspectral image is generated using a second image. A first pixel of the first hyperspectral image has a first pixel value corresponding to a local value obtained using image analysis on a tile in the first image. A second pixel of the second hyperspectral image has a second pixel value corresponding to a local value calculated from a tile in the second image. A third hyperspectral image is generated by combining the first and second hyperspectral images. The third hyperspectral image is then displayed on a computer monitor using a false-color encoding generated using the first and second pixel values.

摘要翻译： 获取组织样本的相邻切片的高分辨率数字图像，并且在图像中定义瓦片。 计算与每个图块中检测到的图像对象相关联的值。 相邻图像中的瓦片共同注册。 使用第一图像生成第一高光谱图像，并且使用第二图像生成第二高光谱图像。 第一高光谱图像的第一像素具有对应于在第一图像中的图块上使用图像分析获得的局部值的第一像素值。 第二高光谱图像的第二像素具有对应于从第二图像中的图块计算的局部值的第二像素值。 通过组合第一和第二高光谱图像来生成第三高光谱图像。 然后，使用使用第一和第二像素值生成的伪色编码，在计算机监视器上显示第三高光谱图像。

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：US09042630B2

公开(公告)日：2015-05-26

申请号：US13282450

申请日：2011-10-26

申请人： Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

发明人： Gerd Binnig ,  Maria Athelogou ,  Guenter Schmidt

IPC分类号： G06K9/00 ,  G06T7/00

CPC分类号： G06T7/0012 ,  G06K9/0014 ,  G06K9/34 ,  G06K9/4652 ,  G06K9/6215 ,  G06T7/11 ,  G06T7/155 ,  G06T7/187 ,  G06T7/90 ,  G06T2207/10024 ,  G06T2207/10056 ,  G06T2207/30024

摘要： A method for determining whether a test biomarker is a stain for a type of cell component, such as membrane or nucleus, involves performing various segmentation processes on an image of tissue stained with the test biomarker. One segmentation process searches for a first cell component type, and another segmentation process searches for a second cell component type by segmenting only stained pixels. The test biomarker is identified as a stain for each component type if the process identifies the component based only on stained pixels. Whether the test biomarker is a membrane stain or nucleus stain is displayed on a graphical user interface. In addition, the method identifies stained pixels corresponding to a second cell component using pixels determined to correspond to a first cell component. An expression profile for the test biomarker is then displayed that indicates the proportion of stained pixels in each type of cell component.

摘要翻译： 用于确定测试生物标志物是否是细胞成分（例如膜或细胞核）类型的污渍的方法包括对用测试生物标志物染色的组织的图像执行各种分割过程。 一个分割过程搜索第一个单元分量类型，另一个分割过程通过仅分割染色的像素来搜索第二单元分量类型。 如果过程仅基于染色的像素识别组分，则将测试生物标志物鉴定为每种组分类型的污点。 测试生物标志物是膜污点还是核染色体显示在图形用户界面上。 此外，该方法使用被确定为对应于第一单元组件的像素来识别与第二单元组件对应的染色像素。 然后显示用于测试生物标志物的表达谱，其指示每种类型细胞组分中染色像素的比例。

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。