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1. 发明授权

US08165369B2 System and method for robust segmentation of pulmonary nodules of various densities 有权
标题翻译：用于各种密度的肺结节的鲁棒分割的系统和方法
公开(公告)号：US08165369B2
公开(公告)日：2012-04-24
申请号：US12243387
申请日：2008-10-01
申请人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
发明人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/187 , G06T2207/30064
摘要： A method for differentiating pulmonary nodules in digitized medical images includes identifying an object of interest from a digital image of the lungs, computing a first distance map of each point of the object of interest, determining a seed point from the first distance map, starting from the seed point, growing a first region by adding successive adjacent layers of points until a background point is reached, and partitioning the first region into a nodule region and a non-nodule region.
摘要翻译：用于区分数字化医学图像中的肺结节的方法包括从肺的数字图像识别感兴趣对象，计算感兴趣对象的每个点的第一距离图，从第一距离图确定种子点，从种子点，通过添加连续的相邻层点直到达到背景点来生长第一区域，并将第一区域划分成结节区域和非结节区域。

2. 发明申请

US20090092302A1 System and Method for Robust Segmentation of Pulmonary Nodules of Various Densities 有权
标题翻译：用于各种密度的肺结节的鲁棒分割的系统和方法
公开(公告)号：US20090092302A1
公开(公告)日：2009-04-09
申请号：US12243387
申请日：2008-10-01
申请人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
发明人： Toshiro Kubota , Anna Jerebko , Marcos Salganicoff
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/187 , G06T2207/30064
摘要： A method for differentiating pulmonary nodules in digitized medical images includes identifying an object of interest from a digital image of the lungs, computing a first distance map of each point of the object of interest, determining a seed point from the first distance map, starting from the seed point, growing a first region by adding successive adjacent layers of points until a background point is reached, and partitioning the first region into a nodule region and a non-nodule region.
摘要翻译：用于区分数字化医学图像中的肺结节的方法包括从肺的数字图像识别感兴趣对象，计算感兴趣对象的每个点的第一距离图，从第一距离图确定种子点，从种子点，通过添加连续的相邻层点直到达到背景点来生长第一区域，并将第一区域划分成结节区域和非结节区域。

3. 发明授权

US07876943B2 System and method for lesion detection using locally adjustable priors 有权
标题翻译：使用局部可调节先验的病变检测系统和方法
公开(公告)号：US07876943B2
公开(公告)日：2011-01-25
申请号：US12241183
申请日：2008-09-30
申请人： Anna Jerebko , Marcos Salganicoff , Maneesh Dewan , Harald Steck
发明人： Anna Jerebko , Marcos Salganicoff , Maneesh Dewan , Harald Steck
IPC分类号： G06K9/00 , A61B5/00
CPC分类号： G06K9/6278 , G06K2209/05 , G06K2209/053 , G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/30028 , G06T2207/30061
摘要： According to an aspect of the invention, a method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of annotated images, each image including one or more candidate regions that have been identified as suspicious, deriving a set of descriptive feature vectors, where each candidate region is associated with a feature vector. A subset of the features are conditionally dependent, and the remaining features are conditionally independent. The conditionally independent features are used to train a naïve Bayes classifier that classifies the candidate regions as lesion or non-lesion. A joint probability distribution that models the conditionally dependent features, and a prior-odds probability ratio of a candidate region being associated with a lesion are determined from the training images. A new classifier is formed from the naïve Bayes classifier, the joint probability distribution, and the prior-odds probability ratio.
摘要翻译：根据本发明的一个方面，一种训练分类器的方法，用于对数字医学图像的计算机辅助诊断中的候选区域进行分类，包括提供注释图像的训练集，每个图像包括已被识别为可疑的一个或多个候选区域，导出一组描述性特征向量，其中每个候选区域与特征向量相关联。特征的子集有条件依赖，其余的特征是有条件的独立的。条件独立的特征用于训练将候选区域分类为病变或非损伤的朴素贝叶斯分类器。从训练图像确定与条件相关特征建模的联合概率分布以及与病变相关联的候选区域的先验概率概率。从初始贝叶斯分类器，联合概率分布和先验概率概率比构成新的分类器。

4. 发明申请

US20090092300A1 System and Method for Lesion Detection Using Locally Adjustable Priors 有权
标题翻译：使用局部可调节的病变检测系统和方法
公开(公告)号：US20090092300A1
公开(公告)日：2009-04-09
申请号：US12241183
申请日：2008-09-30
申请人： Anna Jerebko , Marcos Salganicoff , Maneesh Dewan , Harald Steck
发明人： Anna Jerebko , Marcos Salganicoff , Maneesh Dewan , Harald Steck
IPC分类号： G06K9/00
CPC分类号： G06K9/6278 , G06K2209/05 , G06K2209/053 , G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/30028 , G06T2207/30061
摘要： According to an aspect of the invention, a method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of annotated images, each image including one or more candidate regions that have been identified as suspicious, deriving a set of descriptive feature vectors, where each candidate region is associated with a feature vector. A subset of the features are conditionally dependent, and the remaining features are conditionally independent. The conditionally independent features are used to train a naïve Bayes classifier that classifies the candidate regions as lesion or non-lesion. A joint probability distribution that models the conditionally dependent features, and a prior-odds probability ratio of a candidate region being associated with a lesion are determined from the training images. A new classifier is formed from the naïve Bayes classifier, the joint probability distribution, and the prior-odds probability ratio.
摘要翻译：根据本发明的一个方面，一种训练分类器的方法，用于对数字医学图像的计算机辅助诊断中的候选区域进行分类，包括提供注释图像的训练集，每个图像包括已被识别为可疑的一个或多个候选区域，导出一组描述性特征向量，其中每个候选区域与特征向量相关联。特征的子集有条件依赖，其余的特征是有条件的独立的。条件独立的特征用于训练将候选区域分类为病变或非损伤的朴素贝叶斯分类器。从训练图像确定与条件相关特征建模的联合概率分布以及与病变相关联的候选区域的先验概率概率。从初始贝叶斯分类器，联合概率分布和先验概率概率比构成新的分类器。

5. 发明授权

US07876938B2 System and method for whole body landmark detection, segmentation and change quantification in digital images 有权
标题翻译：数字图像全身地标检测，分割和变化量化的系统和方法
公开(公告)号：US07876938B2
公开(公告)日：2011-01-25
申请号：US11542477
申请日：2006-10-03
申请人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
发明人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
IPC分类号： G06K9/00 , G06K9/62
CPC分类号： G06T7/174 , G06T7/155 , G06T7/33 , G06T7/38 , G06T2207/10072 , G06T2207/20016 , G06T2207/20081 , G06T2207/20164 , G06T2207/30004 , G06T2207/30204
摘要： A method for segmenting digitized images includes providing a training set comprising a plurality of digitized whole-body images, providing labels on anatomical landmarks in each image of said training set, aligning each said training set image, generating positive and negative training examples for each landmark by cropping the aligned training volumes into one or more cropping windows of different spatial scales, and using said positive and negative examples to train a detector for each landmark at one or more spatial scales ranging from a coarse resolution to a fine resolution, wherein the spatial relationship between a cropping windows of a coarse resolution detector and a fine resolution detector is recorded.
摘要翻译：用于分割数字化图像的方法包括提供包括多个数字化的全身图像的训练集合，在所述训练集合的每个图像中的解剖学标志上提供标签，对准每个所述训练集合图像，为每个界标生成正和负训练样本通过将对准的训练量裁剪成不同空间尺度的一个或多个裁剪窗口，并且使用所述正和负的示例来在从粗分辨率到精细分辨率的一个或多个空间尺度上训练每个地标的检测器，其中空间记录粗分辨率检测器的裁切窗与精细分辨率检测器之间的关系。

6. 发明申请

US20070081712A1 System and method for whole body landmark detection, segmentation and change quantification in digital images 有权
标题翻译：数字图像全身地标检测，分割和变化量化的系统和方法
公开(公告)号：US20070081712A1
公开(公告)日：2007-04-12
申请号：US11542477
申请日：2006-10-03
申请人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
发明人： Xiaolei Huang , Xiang Zhou , Anna Jerebko , Arun Krishnan , Haiying Guan , Toshiro Kubota , Vaclav Potesil
IPC分类号： G06K9/00
CPC分类号： G06T7/174 , G06T7/155 , G06T7/33 , G06T7/38 , G06T2207/10072 , G06T2207/20016 , G06T2207/20081 , G06T2207/20164 , G06T2207/30004 , G06T2207/30204
摘要： A method for segmenting digitized images includes providing a training set comprising a plurality of digitized whole-body images, providing labels on anatomical landmarks in each image of said training set, aligning each said training set image, generating positive and negative training examples for each landmark by cropping the aligned training volumes into one or more cropping windows of different spatial scales, and using said positive and negative examples to train a detector for each landmark at one or more spatial scales ranging from a coarse resolution to a fine resolution, wherein the spatial relationship between a cropping windows of a coarse resolution detector and a fine resolution detector is recorded.
摘要翻译：用于分割数字化图像的方法包括提供包括多个数字化的全身图像的训练集合，在所述训练集合的每个图像中的解剖学标志上提供标签，对准每个所述训练集合图像，为每个界标生成正和负训练样本通过将对准的训练量裁剪成不同空间尺度的一个或多个裁剪窗口，并且使用所述正和负的示例来在从粗分辨率到精细分辨率的一个或多个空间尺度上训练每个地标的检测器，其中空间记录粗分辨率检测器的裁切窗与精细分辨率检测器之间的关系。

7. 发明授权

US09113796B2 Method and device for adjusting the visualization of volume data of an object 有权
标题翻译：用于调整物体的体数据的可视化的方法和装置
公开(公告)号：US09113796B2
公开(公告)日：2015-08-25
申请号：US13487227
申请日：2012-06-03
申请人： Klaus Engel , Anna Jerebko
发明人： Klaus Engel , Anna Jerebko
IPC分类号： G06K9/00 , A61B6/02 , G06T15/08 , A61B6/03 , A61B6/00 , A61B8/08 , A61B8/13 , A61B8/00
CPC分类号： A61B6/025 , A61B6/03 , A61B6/037 , A61B6/4441 , A61B6/463 , A61B6/466 , A61B6/469 , A61B6/502 , A61B6/5217 , A61B6/5223 , A61B8/0825 , A61B8/13 , A61B8/463 , G06T15/08
摘要： An adjustment of the visualization of volume data of an object as an image with regard to diagnostically relevant medical information relating to the environment of a region under investigation is provided. In the process, at least one slice region is specified in accordance with slice information within the volume data. A first mapping of a value range of the volume data is used for visualizing the at least one slice region on a display. A second mapping different from the first mapping is used for visualizing a region bordering on the at least one slice region on the display.
摘要翻译：提供了关于与正在调查的区域的环境有关的诊断上相关的医学信息作为图像的对象的体数据的可视化的调整。在该过程中，根据卷数据内的切片信息指定至少一个切片区域。卷数据的值范围的第一映射用于可视化显示器上的至少一个片区域。使用与第一映射不同的第二映射来可视化与显示器上的至少一个片区域邻接的区域。

8. 发明授权

US08705690B2 Imaging method with improved display of a tissue region, imaging device, and computer program product 有权
标题翻译：具有改进的组织区域显示，成像装置和计算机程序产品的成像方法
公开(公告)号：US08705690B2
公开(公告)日：2014-04-22
申请号：US13358081
申请日：2012-01-25
申请人： Anna Jerebko , Klaus Engel
发明人： Anna Jerebko , Klaus Engel
IPC分类号： A61B6/04
CPC分类号： A61B6/025 , A61B6/0414 , A61B6/4452 , A61B6/463 , A61B6/469 , A61B6/502 , A61B6/5223 , G06T11/006 , G06T19/00 , G06T2219/028
摘要： An imaging method with an improved display of a tissue region generates a first visualization and a second visualization from projection recordings that were recorded at different angles. A radiologist is enabled to mark a region in the first visualization, which region is displayed by way of the second visualization.
摘要翻译：具有改进的组织区域显示的成像方法从以不同角度记录的投影记录产生第一可视化和第二可视化。放射科医生能够标记第一可视化中的区域，该区域通过第二可视化显示。

9. 发明授权

US08594407B2 Plane-by-plane iterative reconstruction for digital breast tomosynthesis 有权
标题翻译：用于数字乳房断层合成的平面迭代重建
公开(公告)号：US08594407B2
公开(公告)日：2013-11-26
申请号：US13365451
申请日：2012-02-03
申请人： Anna Jerebko , Koen Michielsen , Johan Nuyts
发明人： Anna Jerebko , Koen Michielsen , Johan Nuyts
IPC分类号： G06K9/00 , A61B6/00
CPC分类号： G06T11/006 , G06T2211/424 , G06T2211/436
摘要： A method for digitally reconstructing a 3-dimensional tomosynthesis image by iterative reconstruction, a reconstructor, and a computer program product method are capable of plane-by-plane iterative reconstruction for digital breast tomosynthesis. The reconstruction process is based on a grouped coordinate ascent algorithm where the volume is split into a plurality of patches, wherein all patches are parallel to a surface of a detector. Splitting the volume allows implementing a modified model for image acquisition where the physical movement of the x-ray source is taken into account because each of the patches is updated separately and sequentially. In addition the splitting allows an efficient implementation on a graphical processing unit by reducing memory requirements.
摘要翻译：通过迭代重建数字重建三维断层合成图像的方法，重建器和计算机程序产品方法能够进行数字乳房层析合成的平面迭代重建。重建过程基于分组的坐标上升算法，其中体积被分成多个斑块，其中所有斑块平行于检测器的表面。拆分音量允许实现用于图像采集的修改模型，其中考虑x射线源的物理移动，因为每个补丁被单独和顺序地更新。此外，拆分允许通过减少内存要求在图形处理单元上有效地实现。

10. 发明授权

US08135189B2 System and method for organ segmentation using surface patch classification in 2D and 3D images 有权
标题翻译：在2D和3D图像中使用表面贴片分类进行器官分割的系统和方法
公开(公告)号：US08135189B2
公开(公告)日：2012-03-13
申请号：US12243327
申请日：2008-10-01
申请人： Anna Jerebko , Matthias Wolf
发明人： Anna Jerebko , Matthias Wolf
IPC分类号： G06K9/00
CPC分类号： G06T17/20 , G06T7/12 , G06T7/149 , G06T2207/10072 , G06T2207/20081 , G06T2207/20124 , G06T2207/30004
摘要： A method for segmenting organs in digitized medical images includes providing a set of segmented training images of an organ, computing a surface mesh having a plurality of mesh cells that approximates a border of the organ, extracting positive examples of all mesh cells and negative examples in the neighborhood of each mesh cell which do not belong to the organ surface, training from the positive examples and negative examples a plurality of classifiers for outputting a probability of a point being a center of a particular mesh cell, computing an active shape model using a subset of center points in the mesh cells, generating a new shape by iteratively deforming the active shape model to fit a test image, and using the classifiers to calculate a probability of each center point of the new shape being a center of a mesh cell which the classifier was trained to recognize.
摘要翻译：用于在数字化医学图像中分割器官的方法包括提供一组器官的分割训练图像，计算具有近似器官边界的多个网格细胞的表面网格，提取所有网孔细胞的阳性实例和阴性实例不属于器官表面的每个网格单元的邻域，从正面示例和负面示例中训练多个分类器，用于输出点是特定网格单元格的中心的概率，使用网格单元中的中心点的子集，通过迭代地使活动形状模型变形以拟合测试图像来生成新形状，并且使用分类器来计算新形状的每个中心点是网格单元格的中心的概率，分类器被训练认识。

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