Method and system for pericardium based model fusion of pre-operative and intra-operative image data for cardiac interventions
    1.
    发明授权
    Method and system for pericardium based model fusion of pre-operative and intra-operative image data for cardiac interventions 有权
    用于心脏干预的手术前和术中图像数据的基于心包的模型融合的方法和系统

    公开(公告)号:US09384546B2

    公开(公告)日:2016-07-05

    申请号:US13765712

    申请日:2013-02-13

    摘要: A method and system for model based fusion pre-operative image data, such as computed tomography (CT), and intra-operative C-arm CT is disclosed. A first pericardium model is segmented in the pre-operative image data and a second pericardium model is segmented in a C-arm CT volume. A deformation field is estimated between the first pericardium model and the second pericardium model. A model of a target cardiac structure, such as a heart chamber model or an aorta model, extracted from the pre-operative image data is fused with the C-arm CT volume based on the estimated deformation field between the first pericardium model and the second pericardium model. An intelligent weighted average may be used improve the model based fusion results using models of the target cardiac structure extracted from pre-operative image data of patients other than a current patient.

    摘要翻译: 公开了一种用于基于模型的融合术前图像数据的方法和系统,例如计算机断层摄影(CT)和手术中C臂CT。 在手术前图像数据中分割第一心包模型,并在C臂CT体积中分割第二心包模型。 在第一心包模型和第二心包模型之间估计变形场。 基于估计的第一心包模型与第二心包模型之间的变形场,将从手术前图像数据提取的目标心脏结构(例如心室模型或主动脉模型)的模型与C臂CT体积融合 心包模型。 可以使用智能加权平均值,使用从当前患者以外的患者的术前图像数据提取的目标心脏结构模型来改进基于模型的融合结果。

    Method and system for model-based fusion of computed tomography and non-contrasted C-arm computed tomography
    5.
    发明授权
    Method and system for model-based fusion of computed tomography and non-contrasted C-arm computed tomography 有权
    计算机断层扫描和非对比C臂计算机断层扫描的基于模型的融合的方法和系统

    公开(公告)号:US09292917B2

    公开(公告)日:2016-03-22

    申请号:US13683224

    申请日:2012-11-21

    IPC分类号: G06K9/00 G06T7/00

    摘要: A method and system for model-based fusion of multi-modal volumetric images is disclosed. A first patient-specific model of an anchor anatomical structure is detected in a first medical image acquired using a first imaging modality, and a second patient-specific model of the anchor anatomical structure is detected in a second medical image acquired using a second imaging modality. A weighted mapping function is determined based on the first patient-specific model of the anchor anatomical structure and the second patient-specific model of the anchor anatomical structure using learned weights to minimize mapping error with respect to a target anatomical structure. The target anatomical structure from the first medical image to the second medical image using the weighted mapping function. In an application of this model-based fusion to transcatheter valve therapies, the trachea bifurcation is used as the anchor anatomical structure and the aortic valve is the target anatomical structure.

    摘要翻译: 公开了一种用于多模态体积图像的基于模型融合的方法和系统。 在使用第一成像模态获取的第一医疗图像中检测锚固解剖结构的第一患者特定模型,并且在使用第二成像模态获取的第二医疗图像中检测锚固解剖结构的第二患者特定模型 。 基于锚解剖结构的第一患者特定模型和使用学习权重的锚定解剖结构的第二患者特定模型来确定加权映射函数,以使关于目标解剖结构的映射误差最小化。 使用加权映射函数从第一医学图像到第二医学图像的目标解剖结构。 在这种基于模型的融合对经导管瓣膜治疗的应用中,气管分叉用作锚固解剖结构,主动脉瓣是目标解剖结构。