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21.
公开(公告)号:US20070041639A1
公开(公告)日:2007-02-22
申请号:US10545656
申请日:2004-02-09
申请人: Jens Von Berg , Michael Kaus
发明人: Jens Von Berg , Michael Kaus
IPC分类号: G06K9/34
CPC分类号: G06T7/0012 , G06T7/12 , G06T7/143 , G06T7/149 , G06T2207/10081 , G06T2207/30004
摘要: Quantification of metric or functional parameters often requires image segmentation. A crucial part of such method is the model of the surface characteristics of the object of interest (features), which drives the deformable surface towards the object boundary in the image. According to the present invention, sections of the mesh are assigned to different classes for different features. According to the present invention, the assignment of mesh sections to the classes is adapted by using actual feature information from the unseen image. Advantageously, this allows for an adaptation of the feature category to which the mesh section is assigned and thereby allows an improved segmentation of the object.
摘要翻译: 度量或功能参数的量化通常需要图像分割。 这种方法的关键部分是感兴趣对象(特征)的表面特征的模型,其驱动可变形表面朝向图像中的对象边界。 根据本发明,将网格的各部分分配给用于不同特征的不同类别。 根据本发明,通过使用来自未知图像的实际特征信息来适应对类的网格部分的分配。 有利地,这允许适配网格部分被分配到的特征类别,从而允许对对象的改进的分割。
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公开(公告)号:US20060126922A1
公开(公告)日:2006-06-15
申请号:US10542094
申请日:2003-12-15
申请人: Jens Von Berg , Vladimir Pekar , Michael Kaus , Olivier Gerard , Jean-Michel Rouet , Sherif Makram-Ebeid , Maxim Fradkin
发明人: Jens Von Berg , Vladimir Pekar , Michael Kaus , Olivier Gerard , Jean-Michel Rouet , Sherif Makram-Ebeid , Maxim Fradkin
CPC分类号: G06T7/0012 , G06T7/12 , G06T7/149 , G06T2207/10072 , G06T2207/30008 , G06T2207/30048
摘要: The invention relates to a method for segmentation of a three-dimensional structure in a three-dimensional data set, especially a medical data set. The method uses a three-dimensional deformable model, wherein the surface of the model consists of a net of polygonal meshes. The meshes are split into groups, and a feature term is assigned to each group. After the model has been placed over the structure of interest, the deformable model is recalculated in consideration of the feature terms of each group.
摘要翻译: 本发明涉及三维数据集,特别是医学数据集中三维结构分割的方法。 该方法使用三维可变形模型,其中模型的表面由多边形网格网组成。 网格被分成组,并且将特征项分配给每个组。 在将模型放置在感兴趣的结构之后,考虑到每个组的特征项,重新计算可变形模型。
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公开(公告)号:US08903153B2
公开(公告)日:2014-12-02
申请号:US13517259
申请日:2010-12-16
申请人: Jens Von Berg , Ulrich Neitzel
发明人: Jens Von Berg , Ulrich Neitzel
CPC分类号: G06T7/0083 , A61B6/5258 , G06T7/12 , G06T2207/10116 , G06T2207/30008
摘要: The invention relates to a system (100) for extracting an object (Ob) from a source image, said object being delineated by a contour (C), the system (100) comprising a gradient unit (110) for computing the source image gradient field, based on the source image, a smoothing unit (120) for smoothing the source image gradient field, and an integration unit (130) for calculating an object image by integrating the smoothed source image gradient field, thereby extracting the object (Ob) from the source image. At each point of the source image, the smoothing is defined by a 2-dimensional convolution kernel which is a product of a first 1-dimensional convolution kernel in the first direction substantially parallel to the contour (C), and a second 1-dimensional convolution kernel in the second direction substantially normal to the contour (C). The first 1-dimensional convolution kernel defines smoothing within each region separated by the contour, while the second 1-dimensional convolution kernel defines smoothing across the contour separating two regions, independently of the orientation of the object and the contour curvature.
摘要翻译: 本发明涉及一种用于从源图像提取对象(Ob)的系统(100),所述对象由轮廓(C)描绘,所述系统(100)包括梯度单元(110),用于计算源图像梯度 字段,基于源图像,平滑源图像梯度场的平滑单元(120),以及用于通过对平滑源图像梯度场进行积分来计算对象图像的积分单元(130),从而提取对象(Ob) 从源图像。 在源图像的每个点处,平滑由二维卷积核定义,二维卷积核是第一方向上基本上平行于轮廓(C)的第一一维卷积核的乘积,第二维 卷积核心在大致垂直于轮廓(C)的第二方向上。 第一个1维卷积内核定义在由轮廓分隔的每个区域内的平滑,而第二个1维卷积内核定义了分离两个区域的轮廓的平滑,独立于物体的方向和轮廓曲率。
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24.
公开(公告)号:US08805073B2
公开(公告)日:2014-08-12
申请号:US10545656
申请日:2004-02-09
申请人: Jens Von Berg , Michael Kaus
发明人: Jens Von Berg , Michael Kaus
IPC分类号: G06K9/24
CPC分类号: G06T7/0012 , G06T7/12 , G06T7/143 , G06T7/149 , G06T2207/10081 , G06T2207/30004
摘要: Quantification of metric or functional parameters often requires image segmentation. A crucial part of such method is the model of the surface characteristics of the object of interest (features), which drives the deformable surface towards the object boundary in the image. According to the present invention, sections of the mesh are assigned to different classes for different features. According to the present invention, the assignment of mesh sections to the classes is adapted by using actual feature information from the unseen image. Advantageously, this allows for an adaptation of the feature category to which the mesh section is assigned and thereby allows an improved segmentation of the object.
摘要翻译: 度量或功能参数的量化通常需要图像分割。 这种方法的关键部分是感兴趣对象(特征)的表面特征的模型,其驱动可变形表面朝向图像中的对象边界。 根据本发明,将网格的各部分分配给用于不同特征的不同类别。 根据本发明,通过使用来自未看见的图像的实际特征信息来适应对类的网格部分的分配。 有利地,这允许适配网格部分被分配到的特征类别,从而允许对对象的改进的分割。
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公开(公告)号:US08798343B2
公开(公告)日:2014-08-05
申请号:US13146885
申请日:2010-01-25
申请人: Sven Kabus , Cristian Lorenz , Nicole Schadewaldt , Roland Opfer , Ingwer Curt Carlsen , Steffen Renisch , Joerg Sabczynski , Hans Barschdorf , Jens Von Berg , Thomas Blaffert , Tobias Klinder
发明人: Sven Kabus , Cristian Lorenz , Nicole Schadewaldt , Roland Opfer , Ingwer Curt Carlsen , Steffen Renisch , Joerg Sabczynski , Hans Barschdorf , Jens Von Berg , Thomas Blaffert , Tobias Klinder
IPC分类号: G06K9/00
CPC分类号: A61B6/5235 , A61B5/08 , A61B6/541 , G06T7/33 , G06T2207/10081 , G06T2207/30061
摘要: A system for displaying lung ventilation information, the system comprising an input (12) and a processing unit (15). The input being provided for receiving multiple CT images (71) of a lung, each CT image (71) corresponding to one phase of at least two different phases in a respiratory cycle. The processing unit (15) being configured to compare CT images (71) corresponding to different phases in the respiratory cycle for determining a deformation vector field for each phase, to generate for each phase a ventilation image (72) based on the corresponding deformation vector field, to spatially align the ventilation images (72), and to generate for at least one common position (62) in each one of the aligned ventilation images (72), a function (81) of a time course of a ventilation value for said common position (62), each ventilation value in the function (81) being based on the deformation vector fields corresponding to the aligned ventilation images (73).
摘要翻译: 一种用于显示肺通气信息的系统,所述系统包括输入(12)和处理单元(15)。 所述输入被提供用于接收肺的多个CT图像(71),每个CT图像(71)对应于呼吸周期中的至少两个不同相的一个相。 所述处理单元(15)被配置为比较对应于呼吸周期中的不同相位的CT图像(71),以确定每个相位的变形矢量场,以根据相应的变形矢量为每个阶段生成通气图像(72) 在空间上对准通气图像(72),并且为每个对齐的通气图像(72)中的至少一个公共位置(62)产生功能(81),其中通风值的时间过程为 所述公共位置(62)中,所述功能(81)中的每个换气值基于对应于对齐的通气图像(73)的变形矢量场。
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公开(公告)号:US20100266173A1
公开(公告)日:2010-10-21
申请号:US12741837
申请日:2008-11-06
申请人: Cristian Lorenz , Jens Von Berg , Thomas Buelow , Rafael Wiemker
发明人: Cristian Lorenz , Jens Von Berg , Thomas Buelow , Rafael Wiemker
IPC分类号: G06K9/00
CPC分类号: G06T7/0012 , G06T7/11 , G06T2200/24 , G06T2207/10072 , G06T2207/30061
摘要: The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention is advantageous in that more efficient computations can be performed because the degree of analysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region. It is thereby possible to increase computational speed and thereby diseases like cancer, in particular cancer nodules in the lungs, can be more effectively found from medical image analysis.
摘要翻译: 本发明涉及用于执行疾病的计算机辅助检测(CAD)的方法,例如, 肺肿瘤,来自成像模态(例如MRI或CT)的医学图像数据集(20)。 最初,使用解剖模型执行医学图像数据集(20)的分割。 其次,对分割的数据进行分析,得到一组分析数据(25),最后分析数据集(25)正在评估疾病。 这些步骤中的至少一个包括用于疾病的位置依赖概率(P_r)作为输入。 本发明的优点在于,可以执行更有效的计算,因为患者部分的某个区域中的分析程度,例如, 肺,可以根据该区域的疾病概率进行调整或调整。 从而可以增加计算速度,从而可以从医学图像分析中更有效地发现像癌症,特别是肺中的癌症结节之类的疾病。
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公开(公告)号:US20100121655A1
公开(公告)日:2010-05-13
申请号:US12516421
申请日:2007-11-22
申请人: Christian Lorenz , Hans Barschdorf , Jens Von Berg , Thomas Blaffert , Sebastian P. M. Dries , Sven Kabus
发明人: Christian Lorenz , Hans Barschdorf , Jens Von Berg , Thomas Blaffert , Sebastian P. M. Dries , Sven Kabus
CPC分类号: G06Q50/24 , G06F19/321 , G06Q50/22 , G16H10/60 , G16H50/50
摘要: A patient data record is described comprising a mean model representative of the patient and further comprises at least one shape model to represent data concerning the patient, in which the said mean model comprises at least one region and the said shape model comprises at least one sub-section, and in which the at least one sub-section of the shape model is linked to the equivalent region of the mean model. This has the advantage of allowing greater structure to the patient record. Further a system is described to present patient data upon queries generated by a user and arranged to access the claimed patient data record, and which is further arranged to provide access to information in the sub-section of the shape model when a query generated by the user accesses the equivalent region of the mean model. This system allows full use of the improved patient data record.
摘要翻译: 描述患者数据记录,其包括代表患者的平均模型,并且还包括至少一个形状模型以表示关于患者的数据,其中所述平均模型包括至少一个区域,并且所述形状模型包括至少一个子 并且其中形状模型的至少一个子部分链接到平均模型的等效区域。 这具有允许病人记录更大结构的优点。 此外,描述了一种系统,用于在由用户生成的查询上呈现患者数据,并且被布置为访问所要求保护的患者数据记录,并且还被设置为当形状模型的子部分中的信息访问时 用户访问平均模型的等效区域。 该系统允许充分利用改进的患者数据记录。
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公开(公告)号:US20100014736A1
公开(公告)日:2010-01-21
申请号:US12438952
申请日:2007-08-27
CPC分类号: G06T7/251 , G06T7/149 , G06T7/33 , G06T2200/04 , G06T2207/10081 , G06T2207/30048 , G06T2207/30061 , G06T2211/412
摘要: The invention relates to a system (100) for adapting a plurality of model meshes to a plurality of image data, the system comprising a registration unit (110) for registering the plurality of model meshes with the plurality of image data on the basis of a computation of a registration transformation for transforming the plurality of model meshes, and an adaptation unit (120) for adapting the plurality of registered model meshes to the plurality of image data on the basis of a computation of locations of mesh vertices of the plurality of model meshes. The system (100) may further comprise a computing unit (130) for computing sparse vector fields comprising vectors of displacements of vertices of the adapted model meshes, an approximation unit (140) for computing dense vector fields on the basis of the sparse vector fields, a merge unit (150) for merging image data sets by means of the computed dense vector fields, and a reconstruction unit (155) for reconstructing a motion-compensated image data from the computed dense vector fields. The described system (100) is capable of reducing motion artifacts in tomographic images computed from data acquired at a plurality of different cardiac cycle phases.
摘要翻译: 本发明涉及一种用于将多个模型网格适配到多个图像数据的系统(100),该系统包括:注册单元(110),用于基于多个图像数据登记多个模型网格与多个图像数据 用于变换多个模型网格的注册变换的计算;以及适应单元,用于根据多个模型的网格顶点的位置的计算来将多个注册模型网格适配到多个图像数据 网格 系统(100)还可以包括计算单元(130),用于计算包括适应模型网格的顶点位移矢量的稀疏矢量场,用于基于稀疏矢量场计算密集矢量场的近似单元(140) ,用于通过所计算的密集矢量场合并图像数据组的合并单元(150),以及用于从所计算的密集矢量场重构运动补偿图像数据的重建单元(155)。 所描述的系统(100)能够减少从在多个不同的心动周期阶段获取的数据计算的断层图像中的运动伪影。
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公开(公告)号:US07440609B2
公开(公告)日:2008-10-21
申请号:US10542094
申请日:2003-12-15
申请人: Jens Von Berg , Vladimir Pekar , Michael Kaus , Olivier Gerard , Jean-Michel Rouet , Sherif Makram-Ebeid , Maxim Fradkin
发明人: Jens Von Berg , Vladimir Pekar , Michael Kaus , Olivier Gerard , Jean-Michel Rouet , Sherif Makram-Ebeid , Maxim Fradkin
CPC分类号: G06T7/0012 , G06T7/12 , G06T7/149 , G06T2207/10072 , G06T2207/30008 , G06T2207/30048
摘要: The invention relates to a method for segmentation of a three-dimensional structure in a three-dimensional data set, especially a medical data set. The method uses a three-dimensional deformable model, wherein the surface of the model consists of a net of polygonal meshes. The meshes are split into groups, and a feature term is assigned to each group. After the model has been placed over the structure of interest, the deformable model is recalculated in consideration of the feature terms of each group.
摘要翻译: 本发明涉及三维数据集,特别是医学数据集中三维结构分割的方法。 该方法使用三维可变形模型,其中模型的表面由多边形网格网组成。 网格被分成组,并且将特征项分配给每个组。 在将模型放置在感兴趣的结构之后,考虑到每个组的特征项,重新计算可变形模型。
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公开(公告)号:US08314792B2
公开(公告)日:2012-11-20
申请号:US12306564
申请日:2007-07-02
申请人: Jens Von Berg , Cristian Lorenz
发明人: Jens Von Berg , Cristian Lorenz
CPC分类号: G06T7/33 , G06T7/20 , G06T2207/10072 , G06T2207/30048
摘要: The invention relates to a system (100) for propagating a model mesh based on a first mean model mesh and on a second mean model mesh, the system comprising: a registration unit (110) for computing a registration transformation for registering the first model mesh with the first mean model mesh; a forward transformation unit (120) for transforming the model mesh into a registered model mesh using the registration transformation; a computation unit (130) for computing a propagation field for propagating the registered model mesh, the propagation field comprising vectors of displacements of vertices of the second mean model mesh relative to respective vertices of the first mean model mesh; a propagation unit (140) for transforming the registered model mesh into the propagated registered model mesh based on applying the vertex displacement vectors comprised in the propagation field to respective vertices of the registered model mesh; and an inverse transformation unit (150) for transforming the propagated registered model mesh into the propagated model mesh using the inverse of the registration transformation, thereby propagating the model mesh. Using the propagation field comprising vectors of displacements of vertices of the second mean model mesh relative to respective vertices of the first mean model mesh improves modeling motion of anatomical shapes. Advantageously, the propagation field of vertex displacement vectors is straightforward to compute and to apply.
摘要翻译: 本发明涉及一种用于基于第一平均模型网格和第二平均模型网格传播模型网格的系统(100),该系统包括:注册单元(110),用于计算用于注册第一模型网格的注册变换 用第一个平均模型网格; 用于使用所述注册变换将所述模型网格变换为注册模型网格的正向变换单元(120) 计算单元(130),用于计算用于传播所述注册的模型网格的传播场,所述传播场包括相对于所述第一平均模型网格的相应顶点的所述第二平均模型网格的顶点的位移的向量; 传播单元,用于通过将包含在传播场中的顶点位移矢量应用于注册的模型网格的各顶点,将登记的模型网格变换为传播的注册模型网格; 以及逆变换单元(150),用于使用所述配准变换的逆来将所述传播的注册模型网格变换为所述传播的模型网格,从而传播所述模型网格。 使用包括相对于第一平均模型网格的各个顶点的第二平均模型网格的顶点的位移的向量的传播场改进了解剖形状的建模运动。 有利地,顶点位移矢量的传播场是直接计算和应用的。
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