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    • 3. 发明申请
    • METHOD AND APPARATUS FOR AUTOMATED DETECTION OF TARGET STRUCTURES FROM MEDICAL IMAGES USING A 3D MORPHOLOGICAL MATCHING ALGORITHM
    • 使用3D形态匹配算法从医学图像自动检测目标结构的方法和装置
    • WO2004049777A2
    • 2004-06-17
    • PCT/US2003/040148
    • 2003-12-03
    • WASHINGTON UNIVERSITYBAE, Kyongtae T.KIM, Jinsung
    • BAE, Kyongtae T.KIM, Jinsung
    • G06K9/00G06T7/00
    • G06T7/0012G06T2207/30061G06T2207/30101
    • A method for the automated detection of target structures shown in digital medical images, the method of comprising: (1) generating a three dimensional (3D) volumetric data set of a patient region within which the target structure resides from a plurality of segmented medical image slices; (2) grouping contiguous structures that are depicted in the 3D volumetric data set to create corresponding grouped structure data sets; (3) assigning each grouped structure data set to one of a plurality of detection algorithms, each detection algorithm being configured to detect a different type of target structure; and (4) processing each grouped structure data set according to its assigned detection algorithm to thereby detect whether any target structures are present in the medical images. Preferably, the target structures are pulmonary nodules, and a specialized detection algorithm is applied to image data classified as a candidate for depicting perivascular nodules. To segment perivascular nodule candidates from surrounding vessels, the image data is preferably correlated with a plurality of 3D morphological filters.
    • 一种用于自动检测数字医学图像中所示的目标结构的方法,所述方法包括:(1)从多个分割的医学图像生成目标结构所在的患者区域的三维(3D)体积数据集 切片; (2)对在3D体积数据集中描绘的连续结构进行分组以产生相应的分组结构数据集; (3)将每个分组结构数据集分配给多个检测算法之一,每个检测算法被配置为检测不同类型的目标结构; 和(4)根据其分配的检测算法处理每个分组的结构数据集,从而检测医学图像中是否存在目标结构。 优选地,靶结构是肺结节,并且将专门的检测算法应用于分类为用于描绘血管周围结节的候选物的图像数据。 为了从周围血管分隔血管周围结节候选物,图像数据优选与多个3D形态滤波器相关。