专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

21. 发明授权

US09014466B2 Region-competitive deformable mesh adaptation 有权
标题翻译：区域竞争变形网格适应
公开(公告)号：US09014466B2
公开(公告)日：2015-04-21
申请号：US11573290
申请日：2005-07-28
申请人： Michael Kaus , Todd R. McNutt , Vladimir Pekar , Matthias Meyer
发明人： Michael Kaus , Todd R. McNutt , Vladimir Pekar , Matthias Meyer
IPC分类号： G06K9/00 , G06T7/00 , A61B6/00 , G06K9/62 , G06T17/20
CPC分类号： G06T7/0083 , A61B6/00 , G06K9/6209 , G06T7/11 , G06T7/12 , G06T7/149 , G06T17/20 , G06T17/205 , G06T2207/10081 , G06T2207/20116 , G06T2207/30008 , G06T2207/30028
摘要： An image segmentation method segments a plurality of image features in an image. The plurality of image features are segmented non-simultaneously in succession. The segmenting of each image feature includes adapting an initial mesh to boundaries of the image feature. The segmenting of each image feature further includes preventing the adapted mesh from overlapping any previously adapted mesh.
摘要翻译：图像分割方法分割图像中的多个图像特征。多个图像特征被连续非同时分割。每个图像特征的分割包括使初始网格适应图像特征的边界。每个图像特征的分割还包括防止适配的网格与任何先前适应的网格重叠。

22. 发明授权

US08787648B2 CT surrogate by auto-segmentation of magnetic resonance images 有权
标题翻译： CT通过磁共振图像的自动分割进行替代
公开(公告)号：US08787648B2
公开(公告)日：2014-07-22
申请号：US12920332
申请日：2009-02-25
申请人： Heinrich Schulz , Michael Kaus , Vladimir Pekar , Torbjoern Vik
发明人： Heinrich Schulz , Michael Kaus , Vladimir Pekar , Torbjoern Vik
IPC分类号： G06K9/00 , A61B6/03 , A61N5/10 , A61B5/055 , G06T7/00 , A61B6/00
CPC分类号： A61N5/103 , A61B5/055 , A61B6/032 , A61B6/037 , A61B6/4417 , A61B6/5247 , G06T7/33 , G06T7/38
摘要： When modeling anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of segmented co-registered CT and MRI anatomical structure reference images can be accessed, and an image of one or more such structures can be selected and overlaid with an MRI image of corresponding structure(s) in a clinical image of a patient. A user can click and drag landmarks or segment edges on the reference MRI image to deform the reference MRI image to align with the patient MRI image. Registration of a landmark in the patient MRI image to the reference MRI image also registers the patient MRI image landmark with a corresponding landmark in the co-registered reference CT image, and electron density information from the reference CT image landmark is automatically attributed to the corresponding registered patient MRI landmark.
摘要翻译：当对用于诊断或治疗计划的患者中的解剖结构进行建模时，可以访问分段共同登记的CT和MRI解剖结构参考图像的图集（26），并且可以选择并覆盖一个或多个这样的结构的图像患者临床图像中相应结构的MRI图像。用户可以点击并拖动参考MRI图像上的地标或段边缘，以使参考MRI图像变形以与患者MRI图像对准。将患者MRI图像中的地标注册到参考MRI图像还将共同登记的参考CT图像中的患者MRI图像标记与相应的标记进行登记，并且来自参考CT图像标记的电子密度信息被自动归因于对应的注册患者MRI地标。

23. 发明授权

US08781254B2 Method, an apparatus and a computer program for data processing 有权
标题翻译：用于数据处理的方法，装置和计算机程序
公开(公告)号：US08781254B2
公开(公告)日：2014-07-15
申请号：US12516357
申请日：2007-11-26
申请人： Stewart Young , Daniel Bystrov , Thomas Netsch , Michael Kaus , Vladimir Pekar
发明人： Stewart Young , Daniel Bystrov , Thomas Netsch , Michael Kaus , Vladimir Pekar
IPC分类号： G06K9/36
CPC分类号： G06T7/149 , G06T7/12 , G06T7/70 , G06T2207/30016
摘要： A method of data processing is provided for estimating a position of an object in an image from a position of a reference object in a reference image. The method includes learning the position of the reference object in the reference image and its relation to a set of reference landmarks in the reference image, accessing the image, accessing the relation between the position of the reference object and the set of the reference landmarks, identifying a set of landmarks in the image corresponding to the set of the reference landmarks, and applying the relation to the set of landmarks in the image for estimating the position of the object in the image.
摘要翻译：提供一种数据处理方法，用于从参考图像中的参考对象的位置估计图像中的对象的位置。该方法包括：在参考图像中学习参考对象的位置及其与参考图像中的一组参考地标的关系，访问图像，访问参考对象的位置与参考地标集合之间的关系，识别对应于所述参考地标集合的图像中的一组地标，以及将所述关系应用于所述图像中的所述地标集合，以估计所述图像中的对象的位置。

24. 发明申请

US20100295848A1 INTERACTIVE IMAGE SEGMENTATION 有权
标题翻译：互动图像分割
公开(公告)号：US20100295848A1
公开(公告)日：2010-11-25
申请号：US12863462
申请日：2009-01-07
申请人： Ruediger Grewer , Sebastian Dries , Daniel Bystrov , Vladimir Pekar , Torbjoern Vik , Heinrich Schulz , Michael Kaus
发明人： Ruediger Grewer , Sebastian Dries , Daniel Bystrov , Vladimir Pekar , Torbjoern Vik , Heinrich Schulz , Michael Kaus
IPC分类号： G06K9/34 , G06T17/00
CPC分类号： G06T7/11 , G06T2207/20101 , G06T2207/20128 , G06T2207/30004
摘要： When adapting models of anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of predesigned anatomical structure models or image volumes can be accessed, and a segmentation of one or more such structures can be selected and overlaid on an a 3D image of corresponding structure(s) in a clinical image (52) of a patient. A user can click on an initially unapproved segmentation 5 landmark (72) on the patient image (52), reposition the unapproved landmark, and approve the repositioned landmark. Remaining unapproved landmarks (72) are then repositioned as a function of the position of the approved landmark (92) using one or more interpolation techniques to adapt the model to the patient image on the fly.
摘要翻译：当适应用于诊断或治疗计划的患者中的解剖结构的模型时，可以访问预先设计的解剖结构模型或图像体积的图集（26），并且可以选择并覆盖在3D上的一个或多个这样的结构的分割在患者的临床图像（52）中的相应结构的图像。用户可以点击患者图像（52）上的最初未被批准的细分5地标（72），重新定位未经批准的地标，并批准重新定位的地标。然后通过使用一种或多种内插技术将剩余的未经批准的地标（72）重新定位为批准的地标（92）的位置的函数，以便将模型随时适应患者图像。

25. 发明授权

US07636461B2 Image-wide artifacts reduction caused by high attenuating objects in ct deploying voxel tissue class 有权
标题翻译：在ct部署体素组织类中由高衰减对象引起的图像范围的伪影减少
公开(公告)号：US07636461B2
公开(公告)日：2009-12-22
申请号：US10597566
申请日：2005-01-24
申请人： Lothar Spies , Celine Saint Olive , Michael Kaus , Vladimir Pekar , Himanshu P. Shukla
发明人： Lothar Spies , Celine Saint Olive , Michael Kaus , Vladimir Pekar , Himanshu P. Shukla
IPC分类号： G06K9/00
CPC分类号： G06T11/008 , G06T2211/424
摘要： A reconstruction processor (34) reconstructs acquired projection data (S) into an uncorrected reconstructed image (T). A classifying algorithm (66) classifies pixels of the uncorrected reconstructed image (T) at least into metal, bone, tissue, and air pixel classes. A clustering algorithm (60) iteratively assigns pixels to best fit classes. A pixel replacement algorithm (70) replaces metal class pixels of the uncorrected reconstructed image (T) with pixel values of the bone density class to generate a metal free image. A morphological algorithm (80) applies prior knowledge of the subject's anatomy to the metal free image to correct the shapes of the class regions to generate a model tomogram image. A forward projector (88) forward projects the model tomogram image to generate model projection data (Smodel). A corrupted rays identifying algorithm (100) identifies the rays in the original projection data (S) which lie through the regions containing metal objects. A corrupted rays replacement algorithm (102) replaces the corrupted regions with corresponding regions of the model projection data to generate corrected projection data (S′). The reconstruction processor (34) reconstructs the corrected projection data (S) into a corrected reconstructed 3D image (T′).
摘要翻译：重建处理器（34）将所获取的投影数据（S）重建成未校正的重建图像（T）。分类算法（66）至少将未校正的重建图像（T）的像素分类为金属，骨骼，组织和空气像素类。聚类算法（60）迭代地将像素分配给最佳拟合类。像素替换算法（70）用未被校正的重建图像（T）的金属类像素替换骨密度类别的像素值，以产生无金属图像。形态学算法（80）将受试者解剖学的先验知识应用于无金属图像，以校正类别区域的形状以产生模型断层图像。向前投影仪（88）向前投影模型断层图像以产生模型投影数据（Smodel）。损坏的光线识别算法（100）识别穿过包含金属物体的区域的原始投影数据（S）中的光线。损坏的光线替换算法（102）将损坏的区域替换为模型投影数据的相应区域，以产生校正投影数据（S'）。重构处理器（34）将经校正的投影数据（S）重建为经校正的重建3D图像（T'）。

26. 发明申请

US20080253635A1 Image-Wide Artifacts Reduction Caused by High Attenuating Objects in Ct Deploying Voxel Tissue Class 有权
标题翻译：在Ct部署体素组织类中由高度衰减对象引起的图像宽的人工减少
公开(公告)号：US20080253635A1
公开(公告)日：2008-10-16
申请号：US10597566
申请日：2005-01-24
申请人： Lothar Spies , Celine Saint Olive , Michael Kaus , Vladimir Pekar , Himanshu P. Shukla
发明人： Lothar Spies , Celine Saint Olive , Michael Kaus , Vladimir Pekar , Himanshu P. Shukla
IPC分类号： G06T11/00
CPC分类号： G06T11/008 , G06T2211/424
摘要： A reconstruction processor (34) reconstructs acquired projection data (S) into an uncorrected reconstructed image (T). A classifying algorithm (66) classifies pixels of the uncorrected reconstructed image (T) at least into metal, bone, tissue, and air pixel classes. A clustering algorithm (60) iteratively assigns pixels to best fit classes. A pixel replacement algorithm (70) replaces metal class pixels of the uncorrected reconstructed image (T) with pixel values of the bone density class to generate a metal free image. A morphological algorithm (80) applies prior knowledge of the subject's anatomy to the metal free image to correct the shapes of the class regions to generate a model tomogram image. A forward projector (88) forward projects the model tomogram image to generate model projection data (Smodel). A corrupted rays identifying algorithm (100) identifies the rays in the original projection data (S) which lie through the regions containing metal objects. A corrupted rays replacement algorithm (102) replaces the corrupted regions with corresponding regions of the model projection data to generate corrected projection data (S). The reconstruction processor (34) reconstructs the corrected projection data (S) into a corrected reconstructed 3D image (T′).
摘要翻译：重建处理器（34）将所获取的投影数据（S）重建成未校正的重建图像（T）。分类算法（66）至少将未校正的重建图像（T）的像素分类为金属，骨骼，组织和空气像素类。聚类算法（60）迭代地将像素分配给最佳拟合类。像素替换算法（70）用未被校正的重建图像（T）的金属类像素替换骨密度类别的像素值，以产生无金属图像。形态学算法（80）将受试者解剖学的先验知识应用于无金属图像，以校正类别区域的形状以产生模型断层图像。前向投影仪（88）向前投影模型断层图像以产生模型投影数据（S 模型）。损坏的光线识别算法（100）识别穿过包含金属物体的区域的原始投影数据（S）中的光线。损坏的光线替换算法（102）将损坏的区域替换为模型投影数据的相应区域，以产生校正的投影数据（S）。重构处理器（34）将经校正的投影数据（S）重建为经校正的重建3D图像（T'）。

27. 发明申请

US20060149511A1 Method of segmenting a three-dimensional data set allowing user corrections 有权
标题翻译：分割允许用户更正的三维数据集的方法
公开(公告)号：US20060149511A1
公开(公告)日：2006-07-06
申请号：US10537883
申请日：2003-12-05
申请人： Michael Kaus , Holger Timinger , Vladimir Pekar
发明人： Michael Kaus , Holger Timinger , Vladimir Pekar
IPC分类号： G06F17/10
CPC分类号： G06T7/149 , G06T7/12 , G06T2207/10081 , G06T2207/20092 , G06T2207/30012
摘要： The invention relates to a method of segmenting a three-dimensional structure from a three-dimensional, and in particular medical, data set while making allowance for user corrections. The method is performed with the help of a deformable three-dimensional model whose surface is formed by a network of nodes and mashes that connect these nodes. Once the model has been positioned at the point in the three-dimensional data set at which the structure to be segmented is situated and positions of nodes have, if necessary, been changed by known methods of segmentation, any desired nodes can be displaced manually. The nodes of the model are recalculated by making weighted allowance for the nodes that have been displaced manually.
摘要翻译：本发明涉及一种从三维特别医疗数据集中分割三维结构同时允许用户校正的方法。该方法借助于可变形的三维模型来执行，该模型的表面由连接这些节点的节点和捣碎网络形成。一旦模型已经被定位在要被分割的结构位于的三维数据集中的位置，并且如果需要，节点的位置已经被已知的分割方法改变，任何期望的节点可以手动移位。通过对已经手动移位的节点进行加权限制来重新计算模型的节点。

28. 发明申请

US20110007959A1 CT SURROGATE BY AUTO-SEGMENTATION OF MAGNETIC RESONANCE IMAGES 有权
标题翻译： CT自动分割磁共振图像
公开(公告)号：US20110007959A1
公开(公告)日：2011-01-13
申请号：US12920332
申请日：2009-02-25
申请人： Heinrich Schulz , Michael Kaus , Vladimir Pekar , Torbjoern Vik
发明人： Heinrich Schulz , Michael Kaus , Vladimir Pekar , Torbjoern Vik
IPC分类号： G06K9/00
CPC分类号： A61N5/103 , A61B5/055 , A61B6/032 , A61B6/037 , A61B6/4417 , A61B6/5247 , G06T7/33 , G06T7/38
摘要： When modeling anatomical structures in a patient for diagnosis or therapeutic planning, an atlas (26) of segmented co-registered CT and MRI anatomical structure reference images can be accessed, and an image of one or more such structures can be selected and overlaid with an MRI image of corresponding structure(s) in a clinical image of a patient. A user can click and drag landmarks or segment edges on the reference MRI image to deform the reference MRI image to align with the patient MRI image. Registration of a landmark in the patient MRI image to the reference MRI image also registers the patient MRI image landmark with a corresponding landmark in the co-registered reference CT image, and electron density information from the reference CT image landmark is automatically attributed to the corresponding registered patient MRI landmark.
摘要翻译：当对用于诊断或治疗计划的患者中的解剖结构进行建模时，可以访问分段共同登记的CT和MRI解剖结构参考图像的图集（26），并且可以选择并覆盖一个或多个这样的结构的图像患者临床图像中相应结构的MRI图像。用户可以点击并拖动参考MRI图像上的地标或段边缘，以使参考MRI图像变形以与患者MRI图像对准。将患者MRI图像中的地标注册到参考MRI图像还将共同登记的参考CT图像中的患者MRI图像标记与相应的标记进行登记，并且来自参考CT图像标记的电子密度信息被自动归因于相应的注册患者MRI地标。

29. 发明申请

US20100061632A1 METHOD, AN APPARATUS AND A COMPUTER PROGRAM FOR DATA PROCESSING 有权
标题翻译：方法，数据处理的装置和计算机程序
公开(公告)号：US20100061632A1
公开(公告)日：2010-03-11
申请号：US12516357
申请日：2007-11-26
申请人： Stewart Young , Daniel Bystrov , Thomas Netsch , Michael Kaus , Vladimir Pekar
发明人： Stewart Young , Daniel Bystrov , Thomas Netsch , Michael Kaus , Vladimir Pekar
IPC分类号： G06K9/34 , G06K9/46
CPC分类号： G06T7/149 , G06T7/12 , G06T7/70 , G06T2207/30016
摘要： The invention relates to a method for data processing. At stage 3 the position of the reference object in the reference image and its relation to a set of reference landmarks in the reference image is established at step 6. In order to enable this, the reference imaging of learning examples may be performed at step 2 and each reference image may be analyzed at step 4, the results may be stored in a suitably arranged database. In order to process the image under consideration, the image is accessed at step 11, the suitable landmark corresponding to the reference landmark in the reference image is identified at step 13 and the spatial relationship established at step 6 is applied to the landmark thereby providing the initial position of the object in the actual image. In case when for the object an imaging volume is selected, the method 1 according to the invention follows to step 7, whereby the scanning 17 is performed within the boundaries given by the thus established scanning volume. In case when for the object a model representative of the target is selected, the method 1 follows to the image segmentation step 19, whereby a suitable segmentation is performed. In case when for the model a deformable model is selected, the segmentation is performed by deforming the model thereby providing spatial boundaries of the target area. The invention further relates to an apparatus and a computer program for image processing.
摘要翻译：本发明涉及一种数据处理方法。在阶段3，在步骤6中建立参考图像中的参考对象的位置及其与参考图像中的一组参考标记的关系。为了实现这一点，可以在步骤2执行学习示例的参考成像并且可以在步骤4分析每个参考图像，结果可以存储在适当布置的数据库中。为了处理所考虑的图像，在步骤11访问图像，在步骤13识别与参考图像中的参考标记相对应的合适地标，并将在步骤6建立的空间关系应用于地标，从而提供物体在实际图像中的初始位置。在对于物体选择成像体积的情况下，根据本发明的方法1遵循步骤7，由此在由这样建立的扫描体积给出的边界内执行扫描17。在针对对象的情况下，选择了表示目标的模型，则对图像分割步骤19进行方法1，由此执行适当的分割。在为模型选择可变形模型的情况下，通过使模型变形从而提供目标区域的空间边界来执行分割。本发明还涉及一种用于图像处理的装置和计算机程序。

30. 发明申请

US20090074264A1 DATA REPRESENTATION FOR RTP 有权
标题翻译： RTP的数据表示
公开(公告)号：US20090074264A1
公开(公告)日：2009-03-19
申请号：US11719781
申请日：2005-11-04
申请人： Vladimir Pekar , Michael Kaus , Ingwer C. Carlsen , Todd R. McNutt , R. Keith Tipton
发明人： Vladimir Pekar , Michael Kaus , Ingwer C. Carlsen , Todd R. McNutt , R. Keith Tipton
IPC分类号： G06K9/00
CPC分类号： A61B6/032 , A61B6/4417 , A61B6/5235 , A61B8/13 , A61B8/4416 , A61N5/103 , A61N5/1039 , G01T1/1611 , G06T7/33 , G06T2207/30004
摘要： An imaging system (10) includes imaging modalities such as a PET imaging system (12) and a CT scanner (14). The CT scanner (14) is used to produce a first image (62) which is used for primary contouring. The PET system (12) is used to provide a second image (56), which provides complementary information about the same or overlapping anatomical region. After first and second images (62, 56) are registered with one another the first and second images (62, 56) are concurrently segmented to outline a keyhole (76). The keyhole portion of the second image (56) is inserted into the keyhole (76) of the first image (62). The user can observe the composite image and deform a boundary (78) of the keyhole (76) by a mouse (52) to better focus on the region of interest within previously defined keyhole.
摘要翻译：成像系统（10）包括诸如PET成像系统（12）和CT扫描仪（14）之类的成像模式。 CT扫描器（14）用于产生用于初级轮廓的第一图像（62）。 PET系统（12）用于提供第二图像（56），其提供关于相同或重叠解剖区域的补充信息。在第一和第二图像（62,56）之间彼此对准之后，第一和第二图像（62,56）被同时分割以勾勒一个键孔（76）。第二图像（56）的锁孔部分插入第一图像（62）的键孔（76）中。用户可以观察合成图像并且通过鼠标（52）使键孔（76）的边界（78）变形以更好地聚焦在先前定义的键孔内的感兴趣区域上。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式