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    • 8. 发明授权
    • System, method and apparatus for small pulmonary nodule computer aided diagnosis from computed tomography scans
    • 用于计算机断层扫描的小型肺结节计算机辅助诊断系统,方法和装置
    • US07499578B2
    • 2009-03-03
    • US10688267
    • 2003-10-17
    • Anthony P. ReevesDavid YankelevitzClaudia HenschkeAntoni Chan
    • Anthony P. ReevesDavid YankelevitzClaudia HenschkeAntoni Chan
    • G06K9/00
    • G06T7/0012G06T3/0075G06T7/44G06T2207/10081G06T2207/30061
    • The present invention is a multi-stage detection algorithm using a successive nodule candidate refinement approach. The detection algorithm involves four major steps. First, the lung region is segmented from a whole lung CT scan. This is followed by a hypothesis generation stage in which nodule candidate locations are identified from the lung region. In the third stage, nodule candidate sub-images pass through a streaking artifact removal process. The nodule candidates are then successively refined using a sequence of filters of increasing complexity. A first filter uses attachment area information to remove vessels and large vessel bifurcation points from the nodule candidate list. A second filter removes small bifurcation points. The invention also improves the consistency of nodule segmentations. This invention uses rigid-body registration, histogram-matching, and a rule-based adjustment system to remove missegmented voxels between two segmentations of the same nodule at different times.
    • 本发明是使用连续结节候选细化方法的多级检测算法。 检测算法涉及四个主要步骤。 首先,从全肺CT扫描分割肺部区域。 随后是从肺区识别结节候选位置的假设生成阶段。 在第三阶段,结节候选子图像通过条纹伪影去除过程。 然后使用逐渐增加的复杂度的一系列滤波器连续地细化结节候选物。 第一个过滤器使用附件区域信息从结节候选列表中移除血管和大血管分叉点。 第二个过滤器移除小分叉点。 本发明还提高了结节分离的一致性。 本发明使用刚体登记,直方图匹配和基于规则的调整系统,以在不同时间去除相同结节的两个分段之间的错误分割的体素。
    • 10. 发明申请
    • System and method for analyzing medical data to determine diagnosis and treatment
    • 用于分析医疗数据以确定诊断和治疗的系统和方法
    • US20060059145A1
    • 2006-03-16
    • US10932443
    • 2004-09-02
    • Claudia HenschkeAnthony ReevesDavid Yankelevitz
    • Claudia HenschkeAnthony ReevesDavid Yankelevitz
    • G06F17/30
    • G06F19/3481G16H10/60
    • Described is a system and method for generating an action plan for diagnosis and treatment of a patient. In particular, a historical database is complied which includes a plurality of records. Each record includes a personal profile and diagnosis data for a person. A plurality of characterizations and corresponding weighting coefficients are derived based on the records in the historical database. Pre-diagnostic patient profile data for a selected patient is obtained for the selected patient. One or more computing modules generate output data for the selected patient as a function of (i) the pre-diagnostic patient profile data, along with the physician's modifications, if any and (ii) the plurality of characterizations and corresponding weighting coefficients. The output data includes at least one of a diagnostic action plan, a confirmation action plan, a confirmation patient profile data and a therapeutic action plan.
    • 描述了一种用于产生用于诊断和治疗患者的动作计划的系统和方法。 特别地,遵循包括多个记录的历史数据库。 每个记录包括一个人的个人资料和诊断数据。 基于历史数据库中的记录导出多个表征和对应的加权系数。 获得所选患者的预诊断患者资料数据。 一个或多个计算模块根据(i)预诊断患者简档数据以及医师的修改(如果有的话)和(ii)多个表征和对应的加权系数,生成所选择的患者的输出数据。 输出数据包括诊断动作计划,确认动作计划,确认患者简档数据和治疗动作计划中的至少一个。