Non-invasive tissue characterization system and method
    21.
    发明授权
    Non-invasive tissue characterization system and method 有权
    非侵入性组织表征系统及方法

    公开(公告)号:US07175597B2

    公开(公告)日:2007-02-13

    申请号:US10356812

    申请日:2003-02-03

    IPC分类号: A61B8/00

    摘要: One embodiment of the present system and method is directed to the identification of tissues within a vascular object by analyzing ultrasound data collected from the vascular object by non-invasive scans. By identifying and characterizing types of tissue from ultrasound data, an assessment can be made about the health condition of a patient without an invasive procedure. Other applications of the present system will also be appreciated including identifying other types of tissues.

    摘要翻译: 本系统和方法的一个实施例涉及通过非侵入性扫描分析从血管对象收集的超声数据来识别血管对象内的组织。 通过从超声数据中识别和表征组织的类型,可以对没有侵入性程序的患者的健康状况进行评估。 还将理解本系统的其它应用,包括识别其他类型的组织。

    Automated lesion analysis based upon automatic plaque characterization according to a classification criterion
    22.
    发明授权
    Automated lesion analysis based upon automatic plaque characterization according to a classification criterion 有权
    根据分类标准,根据自动斑块表征进行自动病变分析

    公开(公告)号:US07627156B2

    公开(公告)日:2009-12-01

    申请号:US11689963

    申请日:2007-03-22

    IPC分类号: G06K9/00 A61B5/05

    摘要: A system and method are disclosed for automatically classifying plaque lesions. A plaque classification application applies a plaque classification criterion to at least one graphical image, comprising a map of spectrally-analyzed characterized tissue of a vessel cross-section, to render an overall plaque classification for the slice or set of slices, covering a 3D volume. The plaque classification is based upon the amount and location of each characterized tissue type (e.g., necrotic core—NC). In an exemplary embodiment the set of potential plaque classifications, not to be confused with characterized tissue types—from which the plaque classifications are derived—include, for example: adaptive intimal thickening (AIT), pathological intimal thickening (PIT), fibroatheroma (FA), thin-cap fibroatheroma (TCFA), and fibro-calcific (FC).

    摘要翻译: 公开了用于自动分类斑块损伤的系统和方法。 斑块分类应用将斑块分类标准应用于至少一个图形图像,其包括血管横截面的光谱分析的特征性组织的图,以呈现切片或切片组的整体斑块分类,覆盖3D体积 。 斑块分类基于每个特征性组织类型(例如,坏死核 - NC)的量和位置。 在一个示例性的实施方案中,不会与斑块分类来源的特征性组织类型混淆的一组潜在斑块分类包括例如:适应性内膜增厚(AIT),病理性内膜增厚(PIT),纤维变性(FA) ),薄盖纤维性肝硬化(TCFA)和纤维钙化(FC)。