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1.发明授权Methods and systems for fast automatic brain matching via spectral correspondence 有权通过频谱对应快速自动脑匹配的方法和系统公开(公告)号：US08965077B2
公开(公告)日：2015-02-24
申请号：US13107002
申请日：2011-05-13
CPC分类号： A61B5/4064 , A61B5/055 , A61B5/72 , A61B2576/026 , G06T7/33 , G06T2200/04 , G06T2207/10088 , G06T2207/20072 , G06T2207/30016
摘要： Methods and systems determine a correspondence of two sets of data, each data set represents an object. A weighted graph is created from each data set, and a Laplacian is determined for each weighted graph, from which spectral components are determined. The spectral components determine a coordinate of a node in a weighted graph. Nodes of a weighted graph are weighted with a quantified feature related to anode. A coordinate related to a quantified feature of a node is added to the coordinate based on the spectral components. Spectral components related to a weighted graph are reordered to a common ordering. Reordered spectral components related to the first and second data set are aligned and a correspondence is determined. An object may be a brain and a feature may be a sulcal depth. Other objects for which a correspondence may be determined include an electrical network, an image and a social network.
摘要翻译： 方法和系统确定两组数据的对应关系，每个数据集表示一个对象。 从每个数据集创建加权图，并为每个加权图确定拉普拉斯算子，从中确定谱分量。 频谱分量确定加权图中节点的坐标。 加权图的节点用与阳极相关的量化特征进行加权。 基于频谱分量将与节点的量化特征相关的坐标添加到坐标。 与加权图相关的光谱分量重新排列为常见的顺序。 将与第一和第二数据集相关的重新排序的频谱分量对齐，并确定一个对应关系。 物体可以是大脑，并且特征可以是平均深度。 可以确定通信的其他对象包括电网，图像和社交网络。
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公开(公告)号：US12042247B2
公开(公告)日：2024-07-23
申请号：US17251306
申请日：2019-06-11
发明人： Atefeh Abdolmanafi , Luc Duong , Nagib Dahdah , Farida Cheriet
IPC分类号： A61B5/00 , G06F18/21 , G06F18/2413 , G06F18/243 , G06N3/08 , G06T7/00 , G06V10/44 , G06V10/764 , G06V10/82 , G16H30/20
CPC分类号： A61B5/0066 , A61B5/0044 , A61B5/7267 , G06F18/21 , G06F18/2413 , G06F18/24323 , G06N3/08 , G06T7/0012 , G06V10/454 , G06V10/764 , G06V10/82 , G16H30/20 , A61B5/0084 , A61B2576/023 , G06T2207/10101 , G06T2207/20081 , G06T2207/20084 , G06T2207/30048 , G06T2207/30101 , G06V2201/03
摘要： There is described a system for determining a coronal artery tissue type. The system generally has an optical coherence tomography (OCT) imaging system being configured for acquiring an OCT image of coronal artery tissue; and a controller configured to perform the steps of: using trained feature extraction engines, extracting corresponding feature vectors comprising a plurality of features in at least a region of interest of the OCT image; using trained classification engines, determining corresponding preliminary coronal artery tissue types associated to the region of interest of the OCT image based on corresponding ones of the plurality of feature vectors; and using a majority voting engine, majority voting an output coronal artery tissue type associated to the region of interest of the OCT image based on the previously determined preliminary coronal artery tissue types.
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3.发明申请METHODS AND SYSTEMS FOR FAST AUTOMATIC BRAIN MATCHING VIA SPECTRAL CORRESPONDENCE 有权通过光谱相关快速自动脑匹配的方法和系统公开(公告)号：US20110295515A1
公开(公告)日：2011-12-01
申请号：US13107002
申请日：2011-05-13
CPC分类号： A61B5/4064 , A61B5/055 , A61B5/72 , A61B2576/026 , G06T7/33 , G06T2200/04 , G06T2207/10088 , G06T2207/20072 , G06T2207/30016
摘要： Methods and systems determine a correspondence of two sets of data, each data set represents an object. A weighted graph is created from each data set, and a Laplacian is determined for each weighted graph, from which spectral components are determined. The spectral components determine a coordinate of a node in a weighted graph. Nodes of a weighted graph are weighted with a quantified feature related to anode. A coordinate related to a quantified feature of a node is added to the coordinate based on the spectral components. Spectral components related to a weighted graph are reordered to a common ordering. Reordered spectral components related to the first and second data set are aligned and a correspondence is determined. An object may be a brain and a feature may be a sulcal depth. Other objects for which a correspondence may be determined include an electrical network, an image and a social network.
摘要翻译： 方法和系统确定两组数据的对应关系，每个数据集表示一个对象。 从每个数据集创建加权图，并为每个加权图确定拉普拉斯算子，从中确定谱分量。 频谱分量确定加权图中节点的坐标。 加权图的节点用与阳极相关的量化特征进行加权。 基于频谱分量将与节点的量化特征相关的坐标添加到坐标。 与加权图相关的光谱分量重新排列为常见的顺序。 将与第一和第二数据集相关的重新排序的频谱分量对齐，并确定一个对应关系。 物体可以是大脑，并且特征可以是平均深度。 可以确定通信的其他对象包括电网，图像和社交网络。
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公开(公告)号：US20080240564A1
公开(公告)日：2008-10-02
申请号：US11927777
申请日：2007-10-30
IPC分类号： G06K9/34
CPC分类号： G06K9/342
摘要： A method for segmenting at least a pair of regions of an image. High resolution data is obtained of the image. Each one of the pair of the regions in the image is marked. Graph cuts are used on the downsampled data to obtain first voxels along an outer boundary of a selected one of the pair of marked regions and second voxels along an inner boundary the selected region. The graphs cuts are projected to the previously obtained high-resolution image data. First and second sets of seeds are placed on the first voxels and a second set of seeds respectively. The first seeds grow into first areas extending inwardly of the selected region while simultaneously the second seeds grow into second areas extending towards the first extending areas until the first areas and the second areas meet to thereby establish the outer boundary of the selected region.
摘要翻译： 一种用于分割图像的至少一对区域的方法。 获得图像的高分辨率数据。 图像中的一对区域中的每一个被标记。 在下采样数据上使用图形切割以沿着所选择的一对标记区域中的所选择的一个的外边界和沿所选区域的内边界的第二体素获得第一体素。 图形切割投影到先前获得的高分辨率图像数据。 第一组和第二组种子分别放置在第一个体素上，第二组种子分别放置在第一个体素上。 第一种子生长到从所选择的区域向内延伸的第一区域中，同时第二种子生长到朝向第一延伸区域延伸的第二区域，直到第一区域和第二区域相交，从而建立所选区域的外边界。
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公开(公告)号：US20210251490A1
公开(公告)日：2021-08-19
申请号：US17251306
申请日：2019-06-11
发明人： Atefeh ABDOLMANAFI , Luc DUONG , Nagib DAHDAH , Farida CHERIET
摘要： There is described a system for determining a coronal artery tissue type. The system generally has an optical coherence tomography (OCT) imaging system being configured for acquiring an OCT image of coronal artery tissue; and a controller configured to perform the steps of: using trained feature extraction engines, extracting corresponding feature vectors comprising a plurality of features in at least a region of interest of the OCT image; using trained classification engines, determining corresponding preliminary coronal artery tissue types associated to the region of interest of the OCT image based on corresponding ones of the plurality of feature vectors; and using a majority voting engine, majority voting an output coronal artery tissue type associated to the region of interest of the OCT image based on the previously determined preliminary coronal artery tissue types.
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公开(公告)号：US08131075B2
公开(公告)日：2012-03-06
申请号：US11927777
申请日：2007-10-30
IPC分类号： G06K9/34
CPC分类号： G06K9/342
摘要： A method for segmenting at least a pair of regions of an image. High resolution data is obtained of the image. Each one of the pair of the regions in the image is marked. Graph cuts are used on the downsampled data to obtain first voxels along an outer boundary of a selected one of the pair of marked regions and second voxels along an inner boundary the selected region. The graphs cuts are projected to the previously obtained high-resolution image data. First and second sets of seeds are placed on the first voxels and a second set of seeds respectively. The first seeds grow into first areas extending inwardly of the selected region while simultaneously the second seeds grow into second areas extending towards the first extending areas until the first areas and the second areas meet to thereby establish the outer boundary of the selected region.
摘要翻译： 一种用于分割图像的至少一对区域的方法。 获得图像的高分辨率数据。 图像中的一对区域中的每一个被标记。 在下采样数据上使用图形切割以沿着所选择的一对标记区域中的所选择的一个的外边界和沿所选区域的内边界的第二体素获得第一体素。 图形切割投影到先前获得的高分辨率图像数据。 第一组和第二组种子分别放置在第一个体素上，第二组种子分别放置在第一个体素上。 第一种子生长到从所选择的区域向内延伸的第一区域中，同时第二种子生长到朝向第一延伸区域延伸的第二区域，直到第一区域和第二区域相交，从而建立所选区域的外边界。
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