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    • 4. 发明申请
    • SYSTEM AND METHOD FOR GROUPING AIRWAYS AND ARTERIES FOR QUANTITATIVE ANALYSIS
    • 用于定量分析的航空和航空分类系统和方法
    • US20070064988A1
    • 2007-03-22
    • US11470294
    • 2006-09-06
    • Benjamin OdryAtilla KiralyCarol Novak
    • Benjamin OdryAtilla KiralyCarol Novak
    • G06K9/00
    • G06T7/0012G06T7/11G06T2207/30101
    • A method for grouping airway and artery pairs, includes: computing a two-dimensional (2D) cross-section of an airway; identifying regions of high-intensity in the 2D cross-section; computing a first indicator for each of the high intensity regions, wherein the first indicator is an orientation measure of the high intensity region with respect to the airway; computing a second indicator for each of the high intensity regions, wherein the second indicator is a circularity measure of the high intensity region; computing a third indicator for each of the high intensity regions, wherein the third indicator is a proximity measure of the high intensity region with respect to the airway; summing the first through third indicators for each of the high intensity regions to obtain a score for each of the high intensity regions; and determining which of the high intensity regions is an artery corresponding to the airway based on its score.
    • 一种用于分组气道和动脉对的方法,包括:计算气道的二维(2D)横截面; 识别2D横截面中高强度的区域; 计算每个所述高强度区域的第一指示符,其中所述第一指示符是所述高强度区域相对于所述气道的取向测量; 计算每个高强度区域的第二指示符,其中第二指示符是高强度区域的圆度度量; 计算每个高强度区域的第三指示符,其中第三指示符是相对于气道的高强度区域的接近度量; 对每个高强度区域的第一至第三指标求和,以获得每个高强度区域的得分; 并且基于其得分确定哪个高强度区域是对应于气道的动脉。
    • 8. 发明申请
    • System and method for detecting a protrusion in a medical image
    • 用于检测医学图像中的突起的系统和方法
    • US20050008205A1
    • 2005-01-13
    • US10849576
    • 2004-05-19
    • Atilla KiralyCarol Novak
    • Atilla KiralyCarol Novak
    • A61B6/03G06F19/00G06T7/00G06K9/00
    • G06T7/0012A61B6/03G06T2207/30028H04N13/128Y10S378/901
    • A system and method for detecting a protrusion in a medical image are provided. The method comprises: acquiring a medical image, wherein the medical image is of an anatomical part; segmenting the medical image; calculating a distance map of the medical image; calculating a gradient of the distance mapped medical image; and processing the gradient to detect a protrusion in the medical image. The gradient is processed by: projecting a plurality of rays from a location in the distance mapped medical image; calculating a value for each of the plurality of rays based on features of each of the plurality of rays and the gradient of the distance mapped medical image; summing and scaling the value of each of the plurality of rays; and detecting one of a sphere-like and polyp-like shape using the summed and scaled values of the plurality of rays, wherein one of the sphere-like and polyp-like shapes is the protrusion.
    • 提供了用于检测医学图像中的突起的系统和方法。 该方法包括:获取医学图像,其中医学图像是解剖部分; 分割医学图像; 计算医学图像的距离图; 计算距离映射医学图像的梯度; 并处理该梯度以检测医用图像中的突起。 通过以下步骤处理梯度:从距离映射的医学图像中的位置投射多条光线; 基于多个射线中的每一个的特征和距离映射医学图像的梯度来计算多个射线中的每一个的值; 对所述多个射线中的每一个的值进行求和和缩放; 并且使用所述多个射线的相加和缩放值来检测球状和息肉状形状之一,其中所述球状和息肉状形状之一是所述突起。