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    • 61. 发明授权
    • Quantitative perfusion analysis
    • 定量灌注分析
    • US09406146B2
    • 2016-08-02
    • US13380610
    • 2010-06-23
    • Rafael WiemkerThomas Buelow
    • Rafael WiemkerThomas Buelow
    • G06K9/00G06T7/40G06T7/20G06T7/00
    • G06T7/401G06T7/0016G06T7/20G06T7/41G06T2207/10096G06T2207/20104G06T2207/30104
    • A system is disclosed for quantitative analysis of perfusion images comprising image elements having intensity values associated therewith. The system comprises a frequency distribution computing subsystem (1) for computing a plurality of frequency distributions of the intensity values of at least part of the images. The system comprises a perfusion information extractor (2) for extracting information relating to perfusion from the plurality of frequency distributions. The perfusion information extractor (2) comprises a shift detector (3) for detecting a shift of the intensity values of the frequency distribution. The perfusion information extractor (2) is arranged for extracting the information relating to perfusion, based on the detected shift. A user interface element (8) enables a user to indicate a boundary between the core region and the rim region by a single degree of freedom. A vesselness subsystem (9) associates a vesselness value with an image element.
    • 公开了一种用于定量分析包括具有与其相关联的强度值的图像元素的灌注图像的系统。 该系统包括用于计算至少部分图像的强度值的多个频率分布的频率分布计算子系统(1)。 该系统包括用于从多个频率分布中提取与灌注相关的信息的灌注信息提取器(2)。 灌注信息提取器(2)包括用于检测频率分布的强度值的偏移的移位检测器(3)。 灌注信息提取器(2)被布置为基于检测到的移位来提取与灌注有关的信息。 用户界面元件(8)使得用户能够通过单个自由度来指示核心区域和边缘区域之间的边界。 容器子系统(9)将容器值与图像元素相关联。
    • 62. 发明授权
    • Segmenting pulmonary arteries
    • 分段肺动脉
    • US08805044B2
    • 2014-08-12
    • US12937289
    • 2009-04-14
    • Thomas BuelowRafael Wiemker
    • Thomas BuelowRafael Wiemker
    • G06K9/00
    • G06T7/162G06T7/33G06T2207/10081G06T2207/20016G06T2207/20072G06T2207/30061G06T2207/30101
    • A method of identifying at least part of a pulmonary artery tree (402) comprises receiving (102) a bronchial tree structure (500) and receiving (104) a pulmonary vessel structure (400). A pair of a first bronchial segment (602) and a first vessel segment (604) is identified (106), wherein the first bronchial segment and the first vessel segment are adjacent with respect to position and orientation. The first vessel segment is identified (108) as arterial segment of the pulmonary artery tree. A spatial transformation is applied (110) such that the first bronchial segment and the first vessel segment substantially coincide (602′). Respective further vessel segments (606, 608) are identified (112) adjacent to bronchial segments (610, 612), wherein the bronchial segments are comprised in the bronchial tree.
    • 识别肺动脉树(402)的至少一部分的方法包括接收(102)支气管树结构(500)并接收(104)肺血管结构(400)。 识别出一对第一支气管段(602)和第一血管段(604)(106),其中第一支气管区段和第一血管区段相对于位置和取向相邻。 识别第一血管段(108)作为肺动脉树的动脉段。 应用空间变换(110)使得第一支气管段和第一血管段基本上重合(602')。 识别与支气管段(610,612)相邻的另外的血管段(606,608),其中支气管段包括在支气管树中。
    • 64. 发明授权
    • Synopsis of multiple segmentation results for breast lesion characterization
    • 乳腺病变特征的多个分割结果的概要
    • US08718341B2
    • 2014-05-06
    • US13131140
    • 2009-11-16
    • Thomas BuelowRafael WiemkerMartin BergtholdtLina Arbash Meinel
    • Thomas BuelowRafael WiemkerMartin BergtholdtLina Arbash Meinel
    • G06K9/00
    • G06T7/0012G06T7/136G06T2207/10096G06T2207/30096
    • When characterizing a tumor or lesion as malignant or benign, a system (10) receives an image of the lesion volume (50), employs a processor (12) to perform a raw segmentation of the image, the results of which are stored to memory (14). Then processor then executes a hole-filling procedure to fill in dark areas in the image of the lesion representing necrotic tissue that absorbed little or no contrast agent, and optionally a leakage removal procedure to remove image voxels associated with non-lesion tissue, e.g., blood vessels, in which the contrast agent was present during imaging, to generate a complete lesion volume. A voxel analyzer (18) assesses a number of voxels included in the raw segmentation of the lesion image, and the final segmentation (e.g., after filling and optional leakage removal). A segmentation comparator (20) computes a ratio of dark area voxels related to necrotic tissue detected after the raw segmentation to total voxels detected in the final image segmentation. The ratio is then used to determine a likelihood of malignancy, with a higher ratio indicating a higher likelihood.
    • 当将肿瘤或病变描绘为恶性或良性时,系统(10)接收病变体积(50)的图像,使用处理器(12)执行图像的原始分割,其结果存储到存储器 (14)。 然后,处理器然后执行填充填充程序以填充代表坏死组织的损伤图像中的暗区域,其吸收很少或没有造影剂,以及可选地泄漏去除程序以去除与非损伤组织相关联的图像体素, 在成像期间存在造影剂的血管,以产生完整的病变体积。 体素分析器(18)评估包括在损伤图像的原始分割中的多个体素,以及最终分割(例如在填充和可选的泄漏移除之后)。 分割比较器(20)计算与原始分割之后检测到的坏死组织相关的暗区域体素与在最终图像分割中检测到的总体素的比率。 然后将该比率用于确定恶性肿瘤的可能性,其中较高的比率表明更高的可能性。
    • 65. 发明申请
    • IMAGE PROCESSING APPARATUS
    • 图像处理设备
    • US20130236124A1
    • 2013-09-12
    • US13988770
    • 2011-11-22
    • Rafael WiemkerThomas BuelowMartin BergtholdtKirsten MeetzIngwer-Curt Carlsen
    • Rafael WiemkerThomas BuelowMartin BergtholdtKirsten MeetzIngwer-Curt Carlsen
    • G06T11/60
    • G06T11/60G06T11/00
    • Image processing apparatus (100) for creating an overlaid presentation of a first input image (101) and a second input image (102) in an output image (108), the first input image comprising input values, the output image comprising vectors of output values, the vectors of output values representing colors of the output image, and the apparatus comprising an input (110) for obtaining the first input put image and the second input image, a rendering unit (140) configured for rendering the first input image in the output image by using a first mapping function for representing the input values in the vectors of output values, a predictor (120) configured for predicting the second input image from the first input image for obtaining a predicted second input image (104), a residual calculator (130) configured for calculating a residual image (106) from the second input image and the predicted second input image, the residual image comprising residual values representing prediction errors of the predicted second input image, and the rendering unit being further configured for rendering the residual image in the output image by using a second mapping function for representing the residual values in the vectors of output values, the second mapping function being different from the first mapping function for distinguishing the residual image from the first input image.
    • 用于在输出图像(108)中创建第一输入图像(101)和第二输入图像(102)的叠加呈现的图像处理装置(100),所述第一输入图像包括输入值,所述输出图像包括输出矢量 值,表示输出图像的颜色的输出值的矢量,以及包括用于获得第一输入放映图像和第二输入图像的输入(110)的装置,被配置为将第一输入图像呈现在 通过使用用于表示输出值的向量中的输入值的第一映射函数的输出图像,配置用于从第一输入图像预测第二输入图像以获得预测的第二输入图像的预测器(120), 剩余计算器(130),被配置为从所述第二输入图像和所述预测的第二输入图像计算残差图像(106),所述残差图像包括表示预测误差的残差值 所述预测的第二输入图像和所述绘制单元还被配置为通过使用用于表示所述输出值的向量中的残差的第二映射函数来呈现所述输出图像中的残差图像,所述第二映射函数不同于所述第一映射 用于区分残差图像与第一输入图像的功能。
    • 67. 发明申请
    • ONE-CLICK CORRECTION OF TUMOR SEGMENTATION RESULTS
    • 一次性修正肿瘤分期结果
    • US20110194742A1
    • 2011-08-11
    • US13123042
    • 2009-10-06
    • Thomas BuelowRafael Wiemker
    • Thomas BuelowRafael Wiemker
    • G06K9/00
    • G06T7/11G06T2200/04G06T2200/24G06T2207/20092G06T2207/30096
    • When adjusting parameters of a segmentation protocol for segmenting a volume of interest in an anatomical image, a user selects a superparameter (50) that includes multiple internal parameters (52) for adjusting a raw segmentation of the volume interest. As a weight of the selected superparameter is adjusted, weights of the internal parameters associated with the superparameter are adjusted according to a superparameter segmentation adjustment algorithm (20). The volume of interest is iteratively re-segmented after each internal parameter adjustment, transparently to the user, until a predetermined amount of change has been effected in the volume of interest segmentation, at which time the re-segmented volume of interest is displayed to the user.
    • 当调整分割协议的参数以分解解剖图像中的感兴趣体积时,用户选择包括多个内部参数(52)的超参数(50),以调整体积兴趣的原始分割。 当调整所选超参数的权重时,根据超参数分段调整算法(20)调整与超参数相关联的内部参数的权重。 在每个内部参数调整之后,对用户透明地重新分段感兴趣的体积,直到感兴趣区段的体积中已经实现了预定量的变化,此时将重新分割的感兴趣体积显示给 用户。