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    • 1. 发明申请
    • SYSTEM AND METHOD FOR BLOOD VESSEL BIFURCATION DETECTION IN THORACIC CT SCANS
    • 胸腔CT扫描血管分支检测系统及方法
    • WO2009070281A2
    • 2009-06-04
    • PCT/US2008/013111
    • 2008-11-25
    • SIEMENS MEDICAL SOLUTIONS USA, INC.PARK, Sangmin
    • PARK, Sangmin
    • G06T7/00A61B5/00
    • G06T7/62G06T7/11G06T7/162G06T7/187G06T2207/10081G06T2207/30101G06T2211/404
    • A method for detecting blood vessel bifurcations in digital medical images includes inflating (61) a sphere from a first center point inside a segmented blood vessel until a surface of the sphere intersects a surface of the blood vessel, searching (62) within the inflated sphere for a second center point that has a sphere intersecting a surface of the blood with a maximum radius, assigning (63) all voxels of the maximal radius sphere to a root node of a shape-tree, increasing (64) the radius of the maximal radius sphere and computing a voxel difference set with respect to the previous maximal radius sphere, computing (65) one or more connected components Cm in the voxel difference set, assigning (67) voxels of each connected components to a different child node of the shape tree, connecting each child node with the root node, and calculating features from the shape tree for training a classifier to detect blood vessel bifurcations.
    • 一种用于检测数字医学图像中的血管分叉的方法包括从分段血管内的第一中心点膨胀(61)球体,直到球体的表面与血管的表面相交,在充气球体内搜索(62) 对于具有与最大半径的血液表面相交的球体的第二中心点,将最大半径球体的所有体素分配(63)到形状树的根节点,增加(64)最大半径的半径 计算(65)体素差异集合中的一个或多个连通分量Cm,将每个连接分量的体素分配给形状的不同子节点(67),并且计算相对于先前最大半径球体设定的体素差异 树,将每个子节点与根节点连接,以及计算来自形状树的特征,以训练分类器以检测血管分叉。
    • 4. 发明申请
    • SYSTEM AND METHOD FOR BLOOD VESSEL BIFURCATION DETECTION IN THORACIC CT SCANS
    • 胸腔CT扫描血管分支检测系统及方法
    • WO2009070281A3
    • 2010-06-03
    • PCT/US2008013111
    • 2008-11-25
    • SIEMENS MEDICAL SOLUTIONSPARK SANGMIN
    • PARK SANGMIN
    • G06T7/00G06T7/60
    • G06T7/62G06T7/11G06T7/162G06T7/187G06T2207/10081G06T2207/30101G06T2211/404
    • A method for detecting blood vessel bifurcations in digital medical images includes inflating (61) a sphere from a first center point inside a segmented blood vessel until a surface of the sphere intersects a surface of the blood vessel, searching (62) within the inflated sphere for a second center point that has a sphere intersecting a surface of the blood with a maximum radius, assigning (63) all voxels of the maximal radius sphere to a root node of a shape-tree, increasing (64) the radius of the maximal radius sphere and computing a voxel difference set with respect to the previous maximal radius sphere, computing (65) one or more connected components Cm in the voxel difference set, assigning (67) voxels of each connected components to a different child node of the shape tree, connecting each child node with the root node, and calculating features from the shape tree for training a classifier to detect blood vessel bifurcations.
    • 一种用于检测数字医学图像中的血管分叉的方法包括从分段血管内的第一中心点膨胀(61)球体,直到球体的表面与血管的表面相交,在充气球体内搜索(62) 对于具有与最大半径的血液表面相交的球体的第二中心点,将最大半径球体的所有体素分配(63)到形状树的根节点,增加(64)最大半径的半径 计算(65)体素差异集合中的一个或多个连通分量Cm,将每个连接分量的体素分配给形状的不同子节点(67),并且计算相对于先前最大半径球体设定的体素差异 树,将每个子节点与根节点连接,以及计算来自形状树的特征,以训练分类器以检测血管分叉。