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公开(公告)号：US08411919B2
公开(公告)日：2013-04-02
申请号：US12496959
申请日：2009-07-02
CPC分类号： G06K9/342 , G06K2009/366 , G06T7/11 , G06T7/149 , G06T2207/10072 , G06T2207/10132 , G06T2207/20101 , G06T2207/30004
摘要： A method for segmenting image data within a data processing system includes acquiring an image. One or more seed points are established within the image. An advection vector field is computed based on image influences and user input. A dye concentration is determined at each of a plurality of portions of the image that results from a diffusion of dye within the computed advection field. The image is segmented into one or more regions based on the determined dye concentration for the corresponding dye.
摘要翻译： 一种用于在数据处理系统内分割图像数据的方法包括获取图像。 在图像内建立一个或多个种子点。 基于图像影响和用户输入计算平流矢量场。 在由计算的对流场内的染料扩散产生的图像的多个部分中的每一个处确定染料浓度。 基于所确定的相应染料的染料浓度，将图像分割成一个或多个区域。
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公开(公告)号：US20100002925A1
公开(公告)日：2010-01-07
申请号：US12496959
申请日：2009-07-02
CPC分类号： G06K9/342 , G06K2009/366 , G06T7/11 , G06T7/149 , G06T2207/10072 , G06T2207/10132 , G06T2207/20101 , G06T2207/30004
摘要： A method for segmenting image data within a data processing system includes acquiring an image. One or more seed points are established within the image. An advection vector field is computed based on image influences and user input. A dye concentration is determined at each of a plurality of portions of the image that results from a diffusion of dye within the computed advection field. The image is segmented into one or more regions based on the determined dye concentration for the corresponding dye.
摘要翻译： 一种用于在数据处理系统内分割图像数据的方法包括获取图像。 在图像内建立一个或多个种子点。 基于图像影响和用户输入计算平流矢量场。 在由计算的对流场内的染料扩散产生的图像的多个部分中的每一个处确定染料浓度。 基于所确定的相应染料的染料浓度，将图像分割成一个或多个区域。
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公开(公告)号：US20090190833A1
公开(公告)日：2009-07-30
申请号：US12362892
申请日：2009-01-30
申请人： Christopher V. Alvino , Leo Grady
发明人： Christopher V. Alvino , Leo Grady
IPC分类号： G06K9/40
CPC分类号： G06K9/40 , G06K9/6207
摘要： A method for recovering a contour using combinatorial optimization includes receiving an input image, initializing functions for gradient f, smooth background g, and contour r, determining an optimum of the gradient f of a region R in the input image, extending the optimum of the gradient f of region R to a complement of R, determining an optimum of the smooth background function g for a region Q corresponding to the complement of R, extending the optimum of the smooth background function g of region Q to a complement of Q, and determining an optimum contour r according to the optimum of the gradient f and the optimum of the smooth background function g.
摘要翻译： 使用组合优化来恢复轮廓的方法包括：接收输入图像，初始化梯度f，平滑背景g和轮廓r的函数，确定输入图像中的区域R的渐变f的最佳值， 区域R到R的补数的梯度f，确定对应于R的补码的区域Q的平滑背景函数g的最优，将区域Q的平滑背景函数g的最优值延伸到Q的补数，以及 根据梯度f的最优值和平滑背景函数g的最优值确定最佳轮廓r。
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4.发明授权Method and system for interactive segmentation using texture and intensity cues 有权使用纹理和强度线索进行交互式分割的方法和系统公开(公告)号：US08331669B2
公开(公告)日：2012-12-11
申请号：US12720753
申请日：2010-03-10
申请人： Yusuf Artan , Leo Grady , Christopher V. Alvino
发明人： Yusuf Artan , Leo Grady , Christopher V. Alvino
IPC分类号： G06K9/34
CPC分类号： G06T7/162 , G06T7/11 , G06T7/143 , G06T2207/20101
摘要： A method for processing image data for segmentation includes receiving image data. One or more seed points are identified within the image data. Intensity and texture features are computer based on the received image data and the seed points. The image data is represented as a graph wherein each pixel of the image data is represented as a node and edges connect nodes representative of proximate pixels of the image data and establishing edge weights for the edges of the graph using a classifier that takes as input, one or more of the computed image features. Graph-based segmentation such as segmentation using the random walker approach may then be performed based on the graph representing the image data.
摘要翻译： 用于处理用于分割的图像数据的方法包括接收图像数据。 在图像数据内识别一个或多个种子点。 强度和纹理特征是基于接收到的图像数据和种子点的计算机。 图像数据被表示为图形，其中图像数据的每个像素被表示为节点，并且边缘连接代表图像数据的邻近像素的节点，并且使用作为输入的分类器为图的边缘建立边缘权重， 一个或多个计算的图像特征。 然后可以基于表示图像数据的图形来执行基于图形的分割，例如使用随机Walker方法的分割。
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公开(公告)号：US08300975B2
公开(公告)日：2012-10-30
申请号：US12362892
申请日：2009-01-30
申请人： Christopher V. Alvino , Leo Grady
发明人： Christopher V. Alvino , Leo Grady
IPC分类号： G06K9/40
CPC分类号： G06K9/40 , G06K9/6207
摘要： A method for recovering a contour using combinatorial optimization includes receiving an input image, initializing functions for gradient f, smooth background g, and contour r, determining an optimum of the gradient f of a region R in the input image, extending the optimum of the gradient f of region R to a complement of R, determining an optimum of the smooth background function g for a region Q corresponding to the complement of R, extending the optimum of the smooth background function g of region Q to a complement of Q, and determining an optimum contour r according to the optimum of the gradient f and the optimum of the smooth background function g.
摘要翻译： 使用组合优化来恢复轮廓的方法包括：接收输入图像，初始化梯度f，平滑背景g和轮廓r的函数，确定输入图像中的区域R的渐变f的最佳值， 区域R到R的补数的梯度f，确定对应于R的补码的区域Q的平滑背景函数g的最优，将区域Q的平滑背景函数g的最优值延伸到Q的补数，以及 根据梯度f的最优值和平滑背景函数g的最优值确定最佳轮廓r。
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公开(公告)号：US09918700B2
公开(公告)日：2018-03-20
申请号：US13928763
申请日：2013-06-27
CPC分类号： A61B8/54 , A61B8/5223 , A61B8/585 , G06F19/00 , G06F19/321 , G16H30/20 , G16H40/63 , G16H50/20
摘要： Values for ultrasound acquisition parameters are altered in a manifold space. The number of parameters to be set is reduced using a manifold. Virtual parameters different than the acquisition parameters are used to alter the greater number of acquisition parameters. In a further use, optimum image settings may be obtained in an automated system by measuring image quality for feeding back to virtual parameter adjustment.
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公开(公告)号：US09594141B2
公开(公告)日：2017-03-14
申请号：US13633908
申请日：2012-10-03
申请人： Daniel Weller , Leo Grady , Lawrence Wald , Vivek K Goyal
发明人： Daniel Weller , Leo Grady , Lawrence Wald , Vivek K Goyal
IPC分类号： G01R33/341 , G01R33/58 , G01R33/561
CPC分类号： G01R33/5611
摘要： An MR imaging system uses multiple RF coils for acquiring corresponding multiple image data sets of a slice or volume of patient anatomy. An image data processor comprises at least one processing device conditioned for, deriving a first set of weights for weighted combination of k-space data of the multiple image data sets for generating a calibration data set comprising a subset of k-space data of composite image data representing the multiple image data sets. The image data processor uses the calibration data set in generating a first MR image data set, deriving the parameters of a probability distribution in response to the first set of weights and the first MR image data set and deriving a second set of weights and second MR image data set together using the probability distribution.
摘要翻译： MR成像系统使用多个RF线圈来获取患者解剖结构的切片或体积的相应的多个图像数据集。 图像数据处理器包括至少一个处理装置，该处理装置被调节为：为多个图像数据集的k空间数据的加权组合推导第一组加权，以产生包括合成图像的k空间数据子集的校准数据集 表示多个图像数据集的数据。 图像数据处理器使用校准数据集来生成第一MR图像数据集，响应于第一组权重和第一MR图像数据集导出概率分布的参数并导出第二组权重和第二MR 使用概率分布将图像数据集合在一起。
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公开(公告)号：US08823374B2
公开(公告)日：2014-09-02
申请号：US13326622
申请日：2011-12-15
IPC分类号： G01V3/00 , G01R33/561
CPC分类号： G01R33/5611
摘要： An MR imaging system uses the multiple RF coils for acquiring corresponding multiple image data sets of the slice. An image data processor comprises at least one processing device conditioned for, generating a composite MR image data set representing a single image in a single non-iterative operation by performing a weighted combination of luminance representative data of individual corresponding pixels of the multiple image data sets in providing an individual pixel luminance value of the composite MR image data set. The image data processor reduces noise in the composite MR image data set by generating a reduced set of significant components in a predetermined transform domain representation of data representing the composite image to provide a de-noised composite MR image data set. An image generator comprises at least one processing device conditioned for, generating a composite MR image using the de-noised composite MR image data set.
摘要翻译： MR成像系统使用多个RF线圈来获取切片的相应多个图像数据集。 图像数据处理器包括至少一个处理装置，该处理装置被调节为：通过执行多个图像数据集合中各个对应像素的亮度代表数据的加权组合来生成在单个非迭代操作中表示单个图像的复合MR图像数据集 提供复合MR图像数据集合的单独像素亮度值。 图像数据处理器通过在表示合成图像的数据的预定变换域表示中生成缩减的重要分量集合来降低复合MR图像数据集中的噪声，以提供去噪复合MR图像数据集。 图像生成器包括至少一个处理装置，该处理装置被调节为使用去噪合成MR图像数据集生成复合MR图像。
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9.发明授权Systems and method for automatic prostate localization in MR images using random walker segmentation initialized via boosted classifiers 有权使用通过增强分类器初始化的随机步行器分割的MR图像中的自动前列腺定位的系统和方法公开(公告)号：US08811701B2
公开(公告)日：2014-08-19
申请号：US13291615
申请日：2011-11-08
申请人： Parmeshwar Khurd , Leo Grady , Ali Kamen , Mamadou Diallo , Kalpitkumar Gajera , Peter Gall , Martin Requardt , Berthold Kiefer , Clifford R. Weiss
发明人： Parmeshwar Khurd , Leo Grady , Ali Kamen , Mamadou Diallo , Kalpitkumar Gajera , Peter Gall , Martin Requardt , Berthold Kiefer , Clifford R. Weiss
CPC分类号： G06K9/6226 , G06T7/11 , G06T7/143 , G06T7/194 , G06T2207/10088 , G06T2207/20081 , G06T2207/20156 , G06T2207/30081
摘要： Automatic prostate localization in T2-weighted MR images facilitate labor-intensive cancer imaging techniques. Methods and systems to accurately segment the prostate gland in MR images are provided and address large variations in prostate anatomy and disease, intensity inhomogeneities, and artifacts induced by endorectal coils. A center of the prostate is automatically detected with a boosted classifier trained on intensity based multi-level Gaussian Mixture Model Expectation Maximization (GMM-EM) segmentations of the raw MR images. A shape model is used in conjunction with Multi-Label Random Walker (MLRW) to constrain the seeding process within MLRW.
摘要翻译： T2加权MR图像中的自动前列腺定位有利于劳动密集型癌症成像技术。 提供了准确分割MR图像前列腺的方法和系统，并解决了前列腺解剖和疾病，强度不均匀性以及直肠内线圈引起的假象的巨大变化。 用基于强度的多级高斯混合模型预期最大化（GMM-EM）原始MR图像分段训练的增强分类器自动检测前列腺的中心。 形状模型与多标签随机Walker（MLRW）结合使用，以限制MLRW内的播种过程。
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公开(公告)号：US20130207652A1
公开(公告)日：2013-08-15
申请号：US13633908
申请日：2012-10-03
申请人： Daniel Weller , Leo Grady , Lawrence Wald , Vivek K. Goyal
发明人： Daniel Weller , Leo Grady , Lawrence Wald , Vivek K. Goyal
IPC分类号： G01R33/341 , G01R33/58
CPC分类号： G01R33/5611
摘要： An MR imaging system uses multiple RF coils for acquiring corresponding multiple image data sets of a slice or volume of patient anatomy. An image data processor comprises at least one processing device conditioned for, deriving a first set of weights for weighted combination of k-space data of the multiple image data sets for generating a calibration data set comprising a subset of k-space data of composite image data representing the multiple image data sets. The image data processor uses the calibration data set in generating a first MR image data set, deriving the parameters of a probability distribution in response to the first set of weights and the first MR image data set and deriving a second set of weights and second MR image data set together using the probability distribution.
摘要翻译： MR成像系统使用多个RF线圈来获取患者解剖结构的切片或体积的相应的多个图像数据集。 图像数据处理器包括至少一个处理装置，该处理装置被调节为：为多个图像数据集的k空间数据的加权组合推导第一组加权，以产生包括合成图像的k空间数据子集的校准数据集 表示多个图像数据集的数据。 图像数据处理器使用校准数据集来生成第一MR图像数据集，响应于第一组权重和第一MR图像数据集导出概率分布的参数并导出第二组权重和第二MR 使用概率分布将图像数据集合在一起。
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