-
公开(公告)号：US09740912B2
公开(公告)日：2017-08-22
申请号：US13330900
申请日：2011-12-20
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.
-
2.发明申请Generating Artificial Hyperspectral Images Using Correlated Analysis of Co-Registered Images 有权使用相关分析共同注册的图像生成人造高光谱图像公开(公告)号：US20130016886A1
公开(公告)日：2013-01-17
申请号：US13546182
申请日：2012-07-11
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。
-
3.发明申请公开(公告)号：US20130156279A1
公开(公告)日：2013-06-20
申请号：US13330900
申请日：2011-12-20
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.
摘要翻译： 用不同生物标志物染色的组织切片的共同对准图像的方法在图形用户界面上显示第一组织切片的第一数字图像，使得第一图像的区域被框包围。 然后显示第二组织切片的第二图像的一部分，使得由帧包围的第一图像的区域与第二图像的显示部分共同对准。 第二图像的显示部分具有该帧的形状。 组织切片是在x和y维度的相应位置处取得的组织样本的z切片。 当用户移动帧下的第一图像时，第二图像的显示部分在x和y维度上移位以与由帧包围的第一图像的区域一致。
-
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
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：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
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。
-
6.发明申请Generating Image-Based Diagnostic Tests By Optimizing Image Analysis and Data Mining Of Co-Registered Images 有权通过优化图像分析和共同注册图像的数据挖掘生成基于图像的诊断测试公开(公告)号：US20170076442A1
公开(公告)日：2017-03-16
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
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.
摘要翻译： 用于生成基于图像的测试的方法通过迭代地修改控制核心图像块的图像和数据分析的规则集来提高诊断精度。 染色的组织切片的数字图像被分割成瓦片，并且来自不同图像的瓦片是核心的。 第一个图像对象链接到图块的所选像素。 通过测量第一个对象来生成第一个数字数据。 热图的每个像素聚集来自核心层的瓦片的第一数值数据。 第二个对象与热图的选定像素相关联。 测量第二个物体产生第二数值数据。 该方法改善了第二数值数据与通过修改用于生成第一和第二对象的规则集以及第一和第二数值数据来分析组织的患者的临床数据相关的程度。 测试由与临床数据产生最佳相关性的那些规则集定义。
-
7.发明授权Generating artificial hyperspectral images using correlated analysis of co-registered images 有权使用共同注册图像的相关分析生成人造高光谱图像公开(公告)号：US08699769B2
公开(公告)日：2014-04-15
申请号：US13546182
申请日：2012-07-11
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：US20110122138A1
公开(公告)日：2011-05-26
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
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。
-
-
-
-
-
-
-
搜索结果
8 条记录 (耗时 0.019 秒)
