公开(公告)号：US20160300346A1

公开(公告)日：2016-10-13

申请号：US15100965

申请日：2013-12-02

Applicant: BRAINLAB AG

Inventor： Stefan Milz ,  Johannes Flake

IPC: G06T7/00 ,  G06K9/62

CPC classification number: G06T7/0012 ,  G06K9/6202 ,  G06T7/344 ,  G06T2207/30061

Abstract: An image transformation method, performed by a computer, for determining a transformation between two medical images of an anatomical structure, respectively taken at a first and second point in time, said method comprising the steps of: acquiring first and second image datasets which represent the first and second image, respectively; determining an image-based transformation between the first image and the second image; acquiring an elastic model of the anatomical structure at the first point in time, wherein the elastic model comprises a plurality of nodes and the relationships between the nodes; calculating the displacements of a subset of the nodes in accordance with the image-based transformation; calculating the displacements of the other nodes in accordance with the relationships between the nodes as represented by the elastic model, while keeping the displacements of the nodes in the subset of nodes constant; and calculating the transformation from the displacement vectors which represent the displacements of the nodes as compared to their positions at the first point in time.

Abstract translation: 一种由计算机执行的用于确定在第一和第二时间点分别获取的解剖结构的两个医学图像之间的变换的图像变换方法，所述方法包括以下步骤：获取第一和第二图像数据集，所述第一和第二图像数据集代表 第一和第二图像; 确定所述第一图像和所述第二图像之间的基于图像的变换; 在第一时间点获取解剖结构的弹性模型，其中弹性模型包括多个节点和节点之间的关系; 根据基于图像的变换计算节点子集的位移; 根据由弹性模型表示的节点之间的关系计算其他节点的位移，同时保持节点子集中的节点的位移不变; 并且从与第一时间点的位置相比较的代表节点的位移的位移矢量计算变换。

公开(公告)号：US09836837B2

公开(公告)日：2017-12-05

申请号：US15100965

申请日：2013-12-02

Applicant: Brainlab AG

Inventor： Stefan Milz ,  Johannes Flake

IPC: G06K9/00 ,  G06T7/00 ,  G06K9/62 ,  G06T7/33

CPC classification number: G06T7/0012 ,  G06K9/6202 ,  G06T7/344 ,  G06T2207/30061

Abstract: An image transformation method, performed by a computer, for determining a transformation between two medical images of an anatomical structure, respectively taken at a first and second point in time, said method comprising the steps of: acquiring first and second image datasets which represent the first and second image, respectively; determining an image-based transformation between the first image and the second image; acquiring an elastic model of the anatomical structure at the first point in time, wherein the elastic model comprises a plurality of nodes and the relationships between the nodes; calculating the displacements of a subset of the nodes in accordance with the image-based transformation; calculating the displacements of the other nodes in accordance with the relationships between the nodes as represented by the elastic model, while keeping the displacements of the nodes in the subset of nodes constant; and calculating the transformation from the displacement vectors which represent the displacements of the nodes as compared to their positions at the first point in time.