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公开(公告)号：US20080089569A1
公开(公告)日：2008-04-17
申请号：US11664759
申请日：2005-10-14
申请人： Padmavathi Sundaram , Daved S. Paik , Eftychis Sifakis , Christopher F. Beaulieu , Ron Fedkiw , Sandy A. Napel
发明人： Padmavathi Sundaram , Daved S. Paik , Eftychis Sifakis , Christopher F. Beaulieu , Ron Fedkiw , Sandy A. Napel
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06T19/20 , G06T2207/30028 , G06T2210/41 , G06T2219/021
摘要： A method of selectively removing folds in a medical image is provided. With this method, a medical image is deformed to straighten and flatten folds but not polyps, thus allowing polyps to be identified. In a first step, a 3-dimensional deformable model of the medical image is constructed. This model is set to have a high Young's modulus and a low Poisson's ratio. In a preferred embodiment, the model is a continuum surface model, preferably a quasistatic continuum finite element model. Once the model has been constructed, it is deformed such that folds are removed but polyps remain, allowing polyps to be identified.
摘要翻译： 提供了选择性地去除医学图像中的褶皱的方法。 利用这种方法，医学图像变形以使折叠变平且不折叠，从而允许识别息肉。 在第一步中，构建医学图像的3维可变形模型。 该模型设计为具有较高的杨氏模量和较低的泊松比。 在优选实施例中，该模型是连续表面模型，优选地是准静态连续体有限元模型。 一旦模型已经构造，它被变形使得折叠被去除但息肉保留，从而允许识别息肉。
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公开(公告)号：US07616800B2
公开(公告)日：2009-11-10
申请号：US11666202
申请日：2005-11-08
IPC分类号： G06T17/40
CPC分类号： G06T19/00 , G06K9/00214 , G06T2210/41 , G16H50/50
摘要： A method of identifying polyps and in a medical image is provided. In a first step, a 3-dimensional model is made of the medical image that contains both polyps (if any were present in the original medical image) and folds. Next, a second 3-dimensional model of the medical image, which is a filtered version of the first model, is constructed in which folds are preserved, but polyps are minimized or eliminated. In a third step, any polyps that were contained in the medical image are identified by subtracting the second 3-dimensional model from the first 3-dimensional model. This subtraction results in a third 3-dimensional model, in which polyps are preserved but folds are minimized or eliminated. With the present inventive method, polyps may be easily and quickly identified without interference from folds.
摘要翻译： 提供了一种识别息肉和医学图像的方法。 在第一步中，三维模型由包含息肉（如果存在于原始医学图像中）和折叠的医学图像构成。 接下来，构建作为第一模型的过滤版本的医学图像的第二三维模型，其中保留折叠，但是息肉被最小化或消除。 在第三步骤中，通过从第一个3维模型中减去第二个三维模型来识别包含在医学图像中的任何息肉。 该减法产生第三个三维模型，其中保留息肉，但折叠被最小化或消除。 利用本发明的方法，可以容易且快速地识别息肉而不受折叠的干扰。
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公开(公告)号：US20080205749A1
公开(公告)日：2008-08-28
申请号：US11893366
申请日：2007-08-14
IPC分类号： G06K9/00
CPC分类号： G06K9/00201 , G06K2209/05
摘要： Improved surface feature recognition in CT images is provided by extracting a triangulated mesh representation of the surface of interest. Shape operators are computed at each vertex of the mesh from finite differences of vertex normals. The shape operators at each vertex are smoothed according to an iterative weighted averaging procedure. Principal curvatures at each vertex are computed from the smoothed shape operators. Vertices are marked as maxima and/or minima according to the signs of the principal curvatures. Vertices marked as having the same feature type are clustered together by adjacency on the mesh to provide candidate patches. Feature scores are computed for each candidate patch and the scores are provided as output to a user or for further processing.
摘要翻译： 通过提取感兴趣的表面的三角网格表示来提供CT图像中改进的表面特征识别。 由顶点法线的有限差异，在网格的每个顶点计算形状运算符。 每个顶点的形状运算符根据迭代加权平均过程进行平滑处理。 从平滑的形状算子计算每个顶点的主曲率。 顶点根据主曲率的符号被标记为最大值和/或最小值。 标记为具有相同特征类型的顶点通过网格上的邻接聚类在一起，以提供候选补丁。 为每个候选补丁计算特征得分，并将得分作为输出提供给用户或用于进一步处理。
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公开(公告)号：US08055047B2
公开(公告)日：2011-11-08
申请号：US11893366
申请日：2007-08-14
IPC分类号： G06K9/00
CPC分类号： G06K9/00201 , G06K2209/05
摘要： Improved surface feature recognition in CT images is provided by extracting a triangulated mesh representation of the surface of interest. Shape operators are computed at each vertex of the mesh from finite differences of vertex normals. The shape operators at each vertex are smoothed according to an iterative weighted averaging procedure. Principal curvatures at each vertex are computed from the smoothed shape operators. Vertices are marked as maxima and/or minima according to the signs of the principal curvatures. Vertices marked as having the same feature type are clustered together by adjacency on the mesh to provide candidate patches. Feature scores are computed for each candidate patch and the scores are provided as output to a user or for further processing.
摘要翻译： 通过提取感兴趣的表面的三角网格表示来提供CT图像中改进的表面特征识别。 由顶点法线的有限差异，在网格的每个顶点计算形状运算符。 每个顶点的形状运算符根据迭代加权平均过程进行平滑处理。 从平滑的形状算子计算每个顶点的主曲率。 顶点根据主曲率的符号被标记为最大值和/或最小值。 标记为具有相同特征类型的顶点通过网格上的邻接聚类在一起，以提供候选补丁。 为每个候选补丁计算特征得分，并将得分作为输出提供给用户或用于进一步处理。
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公开(公告)号：US20080310693A1
公开(公告)日：2008-12-18
申请号：US11666202
申请日：2005-11-08
IPC分类号： G06K9/00
CPC分类号： G06T19/00 , G06K9/00214 , G06T2210/41 , G16H50/50
摘要： A method of identifying polyps and in a medical image is provided. In a first step, a 3-dimensional model is made of the medical image that contains both polyps (if any were present in the original medical image) and folds. Next, a second 3-dimensional model of the medical image, which is a filtered version of the first model, is constructed in which folds are preserved, but polyps are minimized or eliminated. In a third step, any polyps that were contained in the medical image are identified by subtracting the second 3-dimensional model from the first 3-dimensional model. This subtraction results in a third 3-dimensional model, in which polyps are preserved but folds are minimized or eliminated. With the present inventive method, polyps may be easily and quickly identified without interference from folds.
摘要翻译： 提供了一种识别息肉和医学图像的方法。 在第一步中，三维模型由包含息肉（如果存在于原始医学图像中）和折叠的医学图像构成。 接下来，构建作为第一模型的过滤版本的医学图像的第二三维模型，其中保留折叠，但是息肉被最小化或消除。 在第三步骤中，通过从第一个3维模型中减去第二个三维模型来识别包含在医学图像中的任何息肉。 该减法产生第三个三维模型，其中保留息肉，但折叠被最小化或消除。 利用本发明的方法，可以容易且快速地识别息肉而不受折叠的干扰。
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6.发明授权Three-dimensional pattern recognition method to detect shapes in medical images 有权三维图案识别方法，用于检测医学图像中的形状公开(公告)号：US07346209B2
公开(公告)日：2008-03-18
申请号：US10676839
申请日：2003-09-30
申请人： Salih B. Gokturk , Carlo Tomasi , Acar Burak , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
发明人： Salih B. Gokturk , Carlo Tomasi , Acar Burak , Christopher F. Beaulieu , Sandy A. Napel , David S. Paik
IPC分类号： G06K9/62
CPC分类号： G06K9/4609 , G06K9/4647 , G06K2209/05 , G06T7/0012 , G06T2207/30028
摘要： A detection and classification method of a shape in a medical image is provided. It is based on generating a plurality of 2-D sections through a 3-D volume in the medical image. In general, there are two steps. The first step is feature estimation to generate shape signatures for candidate volumes containing candidate shapes. The feature estimation method computes descriptors of objects or of their images. The second general step involves classification of these shape signatures for diagnosis. A classifier contains, builds and/or trains a database of descriptors for previously seen shapes, and then maps descriptors of novel images to categories corresponding to previously seen shapes or classes of shapes.
摘要翻译： 提供了医疗图像中的形状的检测和分类方法。 它基于在医学图像中通过3-D体积产生多个2-D部分。 一般来说，有两个步骤。 第一步是为包含候选形状的候选卷生成形状签名的特征估计。 特征估计方法计算对象或其图像的描述符。 第二个一般步骤包括对这些形状特征进行分类以进行诊断。 分类器包含，构建和/或训练先前看到的形状的描述符数据库，然后将新颖图像的描述符映射到与以前看到的形状或类别形状对应的类别。
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公开(公告)号：US07224827B2
公开(公告)日：2007-05-29
申请号：US10673089
申请日：2003-09-26
IPC分类号： G06K9/00
CPC分类号： G06T3/40 , G06T7/33 , G06T7/38 , G06T2207/30028
摘要： An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine/prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and/or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.
摘要翻译： 提供了一种用于登记倾斜和仰卧计算机断层摄影结肠镜数据的自动方法。 该方法提高了放射科医师的整体解读效率，并为自动结合仰卧/俯卧式计算机辅助检测结果提供依据。 该方法包括确定结肠的相对静止点（仰卧位和俯仰位置）匹配的冒号的（集中）路径或轴。 仰卧位或倾斜路径的伸展和/或收缩都会执行这些点的注册。 匹配和注册以迭代和递归的方式进行，并且基于一个或多个决策标准被认为是完成的。
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8.发明授权Method for detecting and classifying a structure of interest in medical images 失效用于检测和分类医学图像中感兴趣的结构的方法公开(公告)号：US07272251B2
公开(公告)日：2007-09-18
申请号：US10676721
申请日：2003-09-30
申请人： Burak Acar , Christopher F. Beaulieu , Salih B. Gokturk , Carlo Tomasi , David S. Paik , R. Brooke Jeffrey, Jr. , Sandy A. Napel
发明人： Burak Acar , Christopher F. Beaulieu , Salih B. Gokturk , Carlo Tomasi , David S. Paik , R. Brooke Jeffrey, Jr. , Sandy A. Napel
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , G06K9/00201 , G06T2207/30028 , G06T2207/30061
摘要： A method to detect and classify a structure of interest in a medical image is provided to enable high specificity without sacrificing the sensitivity of detection. The method is based on representing changes in three-dimensional image data with a vector field, characterizing the topology of this vector field and using the characterized topology of the vector field for classification of a structure of interest. The method could be used as a stand-alone method or as a post-processing method to enhance and classify outputs of a high-sensitivity low-specificity method to eliminate false positives.
摘要翻译： 提供了一种用于检测和分类医学图像中感兴趣的结构的方法，以实现高特异性而不牺牲检测的灵敏度。 该方法基于用矢量场表示三维图像数据的变化，表征该矢量场的拓扑，并且使用矢量场的表征拓扑来分类感兴趣的结构。 该方法可用作独立方法或作为后处理方法来增强和分类高灵敏度低特异性方法的输出以消除假阳性。
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公开(公告)号：US07043064B2
公开(公告)日：2006-05-09
申请号：US10138113
申请日：2002-05-03
IPC分类号： G06K9/00
CPC分类号： G06K9/48 , G06K2209/053 , G06T7/0012 , Y10S128/922
摘要： A computer-implemented method for determining and characterizing, which portions or shapes of a medical image correspond to a shape of interest is provided. A candidate shape is obtained after which a visible surface is computed adjacent to this candidate shape. A visible surface includes one or more portions of the medical image that are visible by the candidate shape. Once the visible surface is determined, parameters of the visible surface are computed. Then the method further includes the step of determining whether the candidate shape corresponds to a shape of interest. The method further includes the step of computing features of the candidate shape and/or classifying the candidate shape. The advantage of the computer-implemented method is that it provides a high detection specificity, i.e. reducing false positives, without sacrificing sensitivity of the detection of a shape of interest.
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10.发明授权公开(公告)号：US07729739B2
公开(公告)日：2010-06-01
申请号：US11000515
申请日：2004-11-29
IPC分类号： A61B6/00
CPC分类号： G06T7/0012 , G06T7/136 , G06T7/64 , G06T7/68 , G06T2207/20152 , G06T2207/30032
摘要： A method for detecting and identifying structures of interest such as colonic polyps or similar structures like lung nodules in volumetric (medical) images data is provided. The method includes obtaining a heat diffusion field (HDF) by applying a heat diffusion scheme to a volume of interest that includes structures. The obtained heat diffusion field is then used for identifying a structure of interest from the structures in the volume of interest using a geometrical analysis of the heat diffusion field. The heat diffusion scheme is, at least partly, governed by non-linear diffusion parameters. The identification includes two parts: (i) the computation of a spherical symmetry parameter, and (ii) the performance of a local analysis of the volume of interest and computation of a triangulization parameter.
摘要翻译： 提供了一种用于在体积（医学）图像数据中检测和识别兴趣结构如结肠息肉或类似结节如肺结节的方法。 该方法包括通过将热扩散方案应用到包括结构的感兴趣体积来获得热扩散场（HDF）。 然后使用所述热扩散场的几何分析，将所获得的热扩散场用于从感兴趣体积中的结构中鉴定感兴趣的结构。 热扩散方案至少部分地由非线性扩散参数控制。 识别包括两部分：（i）球面对称参数的计算，以及（ii）感兴趣体积的局部分析和三角化参数的计算的性能。
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