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11. 发明授权

US07724954B2 Method and system for interactive image segmentation 有权
标题翻译：交互式图像分割的方法和系统
公开(公告)号：US07724954B2
公开(公告)日：2010-05-25
申请号：US11591767
申请日：2006-11-02
申请人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
发明人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
IPC分类号： G06K9/34
CPC分类号： G06K9/6226 , G06K9/38 , G06K9/6207
摘要： A method for segmentation of an image interactively with a user utilizes level set segmentation and includes selecting by user input respective areas of object and of background; initializing an embedding function implementing a segmentation boundary according to the selecting; computing intensity distributions and for the respective areas of object and of background; and performing repeatedly the steps below until convergence is reached: (a) evolving the embedding function, (b) recomputing the intensity distributions, and (c) checking for new user input and, if so: (d) updating labeling of the areas of object and background.
摘要翻译：用于与用户交互地分割图像的方法利用水平集分割，并且包括通过用户输入选择对象和背景的相应区域; 根据选择初始化实现分割边界的嵌入功能; 计算强度分布和对象和背景的各个区域; 并重复执行以下步骤直到达到融合：（a）演进嵌入功能，（b）重新计算强度分布，（c）检查新的用户输入，如果是：（d）更新标签的区域对象和背景。

12. 发明授权

US07570738B2 Four-dimensional (4D) image verification in respiratory gated radiation therapy 有权
标题翻译：呼吸门控放射治疗四维（4D）图像验证
公开(公告)号：US07570738B2
公开(公告)日：2009-08-04
申请号：US11831090
申请日：2007-07-31
申请人： Ali Khamene , Charles Henri Florin , Juan Carlos Celi , Barbara Ofstad , Mikael Rousson , Frank Sauer , Christian Schaller
发明人： Ali Khamene , Charles Henri Florin , Juan Carlos Celi , Barbara Ofstad , Mikael Rousson , Frank Sauer , Christian Schaller
IPC分类号： A61N5/10 , A61B6/02 , A61B6/03
CPC分类号： A61N5/1049 , A61B5/113 , A61B5/1135 , A61B6/032 , A61B6/541 , A61N5/1037 , A61N5/1064 , A61N5/1068 , A61N2005/1059 , A61N2005/1061 , A61N2005/1062
摘要： A method for four-dimensional (4D) image verification in respiratory gated radiation therapy, includes: acquiring 4D computed tomography (CT) images, each of the 4D CT images representing a breathing phase of a patient and tagged with a corresponding time point of a first surrogate signal; acquiring fluoroscopic images of the patient under free breathing, each of the fluoroscopic images tagged with a corresponding time point of a second surrogate signal; generating digitally reconstructed radiographs (DRRs) for each breathing phase represented by the 4D CT images; generating a similarity matrix to assess a degree of resemblance in a region of interest between the DRRs and the fluoroscopic images; computing a compounded similarity matrix by averaging values of the similarity matrix across different time points of the breathing phase during a breathing period of the patient; determining an optimal time point synchronization between the DRRs and the fluoroscopic images by using the compounded similarity matrix; and acquiring a third surrogate signal and turning a treatment beam on or off according to the optimal time point synchronization.
摘要翻译：呼吸门控放射治疗中四维（4D）图像验证的方法包括：获取4D计算机断层摄影（CT）图像，每个4D CT图像代表患者的呼吸阶段，并用相应的时间点标记第一替代信号; 在自由呼吸下获取患者的透视图像，每个透视图像标记有第二替代信号的相应时间点; 为由4D CT图像表示的每个呼吸阶段生成数字重建X射线照片（DRR）; 生成相似性矩阵以评估DRR和荧光透视图像之间的感兴趣区域中的相似程度; 通过在患者的呼吸期间在呼吸阶段的不同时间点平均相似性矩阵的值来计算复合相似性矩阵; 通过使用复合相似度矩阵确定DRR和荧光透视图像之间的最佳时间点同步; 并根据最佳时间点同步获取第三替代信号并打开或关闭治疗束。

13. 发明授权

US07424153B2 Shape priors for level set representations 有权
标题翻译：形成级别表示的先验
公开(公告)号：US07424153B2
公开(公告)日：2008-09-09
申请号：US11508794
申请日：2006-08-23
申请人： Nikolaos Paragios , Mikael Rousson
发明人： Nikolaos Paragios , Mikael Rousson
IPC分类号： G06K9/62
CPC分类号： G06K9/00362 , G06K9/48 , G06K9/6206 , G06T7/12 , G06T7/149
摘要： This invention relates to shape priors for level set representations. An embodiment of the invention comprises a first stage and a second stage. In the first stage, a shape model can be built directly on level set space using a collection of samples. The shape model can be constructed using a variational framework to create a non-stationary pixel-wise model that accounts for shape variabilities. Then, in the second stage, the shape model can be used as basis to introduce the shape prior in an energetic form. In terms of level set representations, the shape prior aims at minimizing non-stationary distance between the evolving interface and the shape model. An embodiment according to the present invention can be integrated with an existing, data-driven variational method to perform image segmentation for physically corrupted and incomplete data.
摘要翻译：本发明涉及水平集表示的形状先验。本发明的实施例包括第一阶段和第二阶段。在第一阶段，可以使用样本集合直接在级别集空间上构建形状模型。可以使用变分框架来构建形状模型，以创建考虑到形状变异性的非平稳像素模型。然后，在第二阶段中，形状模型可以用作以能量形式引入形状的基础。在水平集表示方面，先前的形状旨在最小化不断变化的界面和形状模型之间的非固定距离。根据本发明的实施例可以与现有的数据驱动变分方法集成，以对物理损坏和不完整的数据执行图像分割。

14. 发明申请

US20080107351A1 EFFICIENT SEGMENTATION OF PIECEWISE SMOOTH IMAGES 有权
标题翻译：高分辨率图像的有效分割
公开(公告)号：US20080107351A1
公开(公告)日：2008-05-08
申请号：US11696869
申请日：2007-04-05
申请人： Jerome Piovano , Mikael Rousson
发明人： Jerome Piovano , Mikael Rousson
IPC分类号： G06K9/44
CPC分类号： G06T7/149 , G06T7/11 , G06T2207/20161
摘要： A fast and robust segmentation model for piecewise smooth images is provided. Local statistics in an energy formulation are provided as a functional. The shape gradient of this new functional gives a contour evolution controlled by local averaging of image intensities inside and outside the contour. Fast computation is realized by expressing terms as the result of convolutions implemented via recursive filters. Results are similar to the general Mumford-Shah model but realized faster without having to solve a Poisson partial differential equation at each iteration. Examples are provided. A system to implement segmentation methods is also provided.
摘要翻译：提供了一种用于分段平滑图像的快速且鲁棒的分割模型。提供能量公式中的本地统计作为功能。这种新功能的形状梯度给出了通过轮廓内部和外部的图像强度的局部平均来控制的轮廓演化。通过表达术语作为通过递归滤波器实现的卷积的结果来实现快速计算。结果与一般的Mumford-Shah模型相似，但实现得更快，而无需在每次迭代中解决泊松偏微分方程。提供了实例。还提供了一种实现分割方法的系统。

15. 发明申请

US20070211940A1 Method and system for interactive image segmentation 有权
标题翻译：交互式图像分割的方法和系统
公开(公告)号：US20070211940A1
公开(公告)日：2007-09-13
申请号：US11591767
申请日：2006-11-02
申请人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
发明人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
IPC分类号： G06K9/34
CPC分类号： G06K9/6226 , G06K9/38 , G06K9/6207
摘要： A method for segmentation of an image interactively with a user utilizes level set segmentation and includes selecting by user input respective areas of object and of background; initializing an embedding function implementing a segmentation boundary according to the selecting; computing intensity distributions and for the respective areas of object and of background; and performing repeatedly the steps below until convergence is reached: (a) evolving the embedding function, (b) recomputing the intensity distributions, and (c) checking for new user input and, if so: (d) updating labeling of the areas of object and background.
摘要翻译：用于与用户交互地分割图像的方法利用水平集分割，并且包括通过用户输入选择对象和背景的相应区域; 根据选择初始化实现分割边界的嵌入功能; 计算强度分布和对象和背景的各个区域; 并重复执行以下步骤直到达到融合：（a）演进嵌入功能，（b）重新计算强度分布，（c）检查新的用户输入，如果是：（d）更新标签的区域对象和背景。

16. 发明授权

US08488873B2 Method of computing global-to-local metrics for recognition 有权
标题翻译：计算用于识别的全局到本地度量的方法
公开(公告)号：US08488873B2
公开(公告)日：2013-07-16
申请号：US12574717
申请日：2009-10-07
申请人： Mikael Rousson , Jan Erik Solem , Jerome Piovano
发明人： Mikael Rousson , Jan Erik Solem , Jerome Piovano
IPC分类号： G06K9/62 , G06K9/00
CPC分类号： G06K9/6215 , G06N99/005
摘要： A method of computing global-to-local metrics for recognition. Based on training examples with feature representations, the method automatically computes a local metric that varies over the space of feature representations to optimize discrimination and the performance of recognition systems.Given a set of points in an arbitrary features space, local metrics are learned in a hierarchical manner that give low distances between points of same class and high distances between points of different classes. Rather than considering a global metric, a class-based metric or a point-based metric, the proposed invention applies successive clustering to the data and associates a metric to each one of the clusters.
摘要翻译：计算用于识别的全局到本地度量的方法。基于具有特征表示的训练示例，该方法自动计算在特征表示空间上变化的局部度量，以优化识别系统的识别和性能。给定任意特征空间中的一组点，以分级方式学习局部度量，这样可以在不同类别的点之间提供相同类别的点和高距离之间的较低距离。所提出的发明不是考虑全局度量，基于类的度量或基于点的度量，而是将连续的聚类应用于数据并将度量与每个集群相关联。

17. 发明申请

US20070003137A1 Efficient kernel density estimation of shape and intensity priors for level set segmentation 失效
标题翻译：用于水平集分割的形状和强度优先级的有效核密度估计
公开(公告)号：US20070003137A1
公开(公告)日：2007-01-04
申请号：US11397040
申请日：2006-04-03
申请人： Daniel Cremers , Mikael Rousson
发明人： Daniel Cremers , Mikael Rousson
IPC分类号： G06K9/34
CPC分类号： G06K9/6207 , G06T7/12 , G06T7/143 , G06T7/149 , G06T2207/10132 , G06T2207/30004
摘要： Methods and systems for image segmentation are disclosed. A nonlinear statistical shape model of an image is integrated with a non-parametric intensity model to estimate characteristics of an image and create segmentations of an image based on Bayesian inference from characteristics of prior learned images based on the same models
摘要翻译：公开了用于图像分割的方法和系统。图像的非线性统计形状模型与非参数强度模型集成以估计图像的特征，并且基于基于相同模型的先前学习图像的特征，基于贝叶斯推理创建图像的分割

18. 发明授权

US07095890B2 Integration of visual information, anatomic constraints and prior shape knowledge for medical segmentations 有权
标题翻译：视觉信息，解剖约束和医学分割的先前形状知识的整合
公开(公告)号：US07095890B2
公开(公告)日：2006-08-22
申请号：US10356455
申请日：2003-01-31
申请人： Nikolaos Paragios , Visvanathan Ramesh , Mikael Rousson
发明人： Nikolaos Paragios , Visvanathan Ramesh , Mikael Rousson
IPC分类号： G06K9/34 , G06K9/00 , G06K9/48
CPC分类号： G06T7/149 , G06T7/12 , G06T2207/10088 , G06T2207/20161 , G06T2207/30048
摘要： This invention relates to the integration of visual information, anatomic constraints, prior shape knowledge, and level set representations for the segmentation of medical images. An embodiment according to the present invention comprises a level set variational framework that uses a bi-directional boundary flow, an intensity-based regional component that maximizes the a posteriori segmentation probability, a physiology-based module that constrains the solution space and a term that accounts for shape-driven consistency. All modules are expressed in an energetic form and the resulting objective function is optimized using a gradient descent method.
摘要翻译：本发明涉及视觉信息，解剖约束，先前形状知识和用于医学图像分割的水平集表示的集成。根据本发明的实施例包括使用双向边界流的水平集变分框架，使后验分割概率最大化的基于强度的区域分量，约束解空间的基于生理学的模块和一个术语，考虑到形状驱动的一致性。所有模块都以能量形式表达，并且使用梯度下降法优化所得到的目标函数。

19. 发明申请

US20110081074A1 Method of Computing Global-to-Local Metrics for Recognition 有权
标题翻译：计算全球到本地度量标准的方法
公开(公告)号：US20110081074A1
公开(公告)日：2011-04-07
申请号：US12574717
申请日：2009-10-07
申请人： Mikael Rousson , Jan Erik Solem , Jerome Piovano
发明人： Mikael Rousson , Jan Erik Solem , Jerome Piovano
IPC分类号： G06K9/62
CPC分类号： G06K9/6215 , G06N99/005
摘要： A method of computing global-to-local metrics for recognition. Based on training examples with feature representations, the method automatically computes a local metric that varies over the space of feature representations to optimize discrimination and the performance of recognition systems.Given a set of points in an arbitrary features space, local metrics are learned in a hierarchical manner that give low distances between points of same class and high distances between points of different classes. Rather than considering a global metric, a class-based metric or a point-based metric, the proposed invention applies successive clustering to the data and associates a metric to each one of the clusters.
摘要翻译：计算用于识别的全局到本地度量的方法。基于具有特征表示的训练示例，该方法自动计算在特征表示空间上变化的局部度量，以优化识别系统的识别和性能。给定任意特征空间中的一组点，以分级方式学习局部度量，这样可以在不同类别的点之间提供相同类别的点和高距离之间的较低距离。所提出的发明不是考虑全局度量，基于类的度量或基于点的度量，而是将连续的聚类应用于数据并将度量与每个集群相关联。

20. 发明授权

US07889922B2 Method and system for histogram calculation using a graphics processing unit 有权
标题翻译：使用图形处理单元进行直方图计算的方法和系统
公开(公告)号：US07889922B2
公开(公告)日：2011-02-15
申请号：US11594460
申请日：2006-11-08
申请人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
发明人： Oliver Fluck , Shmuel Aharon , Mikael Rousson , Daniel Cremers
IPC分类号： G06K9/00 , G06F17/00 , G06F15/80 , G06T1/00 , G06T1/60
CPC分类号： G06T1/20
摘要： A method for histogram calculation using a graphics processing unit (GPU), comprises storing image data in a two-dimensional (2D) texture domain; subdividing the domain into independent regions or tiles; calculating in parallel, in a GPU, a plurality of tile histograms, one for each tile; and summing up in parallel, in the GPU, the tile histograms so as to derive a final image histogram.
摘要翻译：一种使用图形处理单元（GPU）进行直方图计算的方法，包括将图像数据存储在二维（2D）纹理域中; 将域细分为独立区域或瓦片; 在GPU中并行计算多个瓦片直方图，每个瓦片一个; 并且在GPU中并行地并行地绘制瓦片直方图，以便导出最终图像直方图。

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