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    • 41. 发明申请
    • Generating an anatomical model using a rule-based segmentation and classification process
    • 使用基于规则的分割和分类过程生成解剖模型
    • US20080292153A1
    • 2008-11-27
    • US11807096
    • 2007-05-25
    • Gerd BinnigGuenter Schmidt
    • Gerd BinnigGuenter Schmidt
    • G06K9/00
    • G06T7/0012G06K9/6268G06T2200/24G06T2207/20108G06T2207/30004
    • A system for computer-aided detection uses a computer-implemented network structure to analyze patterns present in digital image slices of a human body and to generate a three-dimensional anatomical model of a patient. The anatomical model is generated by detecting easily identifiable organs first and then using those organs as context objects to detect other organs. A user specifies membership functions that define which objects of the network structure belong to the various classes of human organs specified in a class hierarchy. A membership function of a potentially matching class determines whether a candidate object of the network structure belongs to the potential class based on the relation between a property of the voxels linked to the candidate object and a property of the context object. Some voxel properties used to classify an object are location, brightness and volume. The human organs are then measured to assist in the patient's diagnosis.
    • 用于计算机辅助检测的系统使用计算机实现的网络结构来分析存在于人体的数字图像切片中的图案并且生成患者的三维解剖模型。 首先通过检测容易识别的器官,然后使用那些器官作为上下文对象来检测其他器官来产生解剖模型。 用户指定隶属函数,其定义网络结构的哪些对象属于在类层次结构中指定的各种人体器官。 潜在匹配类的隶属函数基于与候选对象链接的体素的属性与上下文对象的属性之间的关系确定网络结构的候选对象是否属于潜在类。 用于分类对象的一些体素属性是位置,亮度和体积。 然后测量人体器官以辅助患者的诊断。
    • 42. 发明申请
    • CASE IMAGE SEARCH APPARATUS AND SYSTEM
    • 案例图像搜索设备和系统
    • US20080240494A1
    • 2008-10-02
    • US12058748
    • 2008-03-30
    • Akira OosawaTakayuki Udagawa
    • Akira OosawaTakayuki Udagawa
    • G06K9/00
    • G06F19/321G06F17/30259G06F19/00G06T7/0012G06T2207/10072G06T2207/20108G06T2207/30061G06T2207/30096G16H50/70
    • An arbitrary cross-sectional image (MPR image) is used as an image for searching a case DB which has registered case images for a case image similar to an image to be diagnosed. A user terminal produces an axial image with reference to a diseased site in the MPR image, the axial image containing the diseased site, calculates a feature value (first feature value) of the diseased site contained in the axial image, and sends the feature value to the case DB. A case image server compares the received first feature value with a feature value (second feature value) for each case registered in a feature value DB, searches the case DB for a case image having a second feature value similar to the first feature value based on the comparison result, and sends the searched case image to the user terminal.
    • 使用任意的截面图像(MPR图像)作为用于搜索具有与要诊断的图像类似的病例图像的病例图像的病例DB的图像。 用户终端参照MPR图像中的患病部位产生轴向图像,包含病变部位的轴向图像计算包含在轴向图像中的病变部位的特征值(第一特征值),并且发送特征值 到案例DB。 病例图像服务器将接收到的第一特征值与登记在特征值DB中的每个病例的特征值(第二特征值)进行比较,基于基于第一特征值的第二特征值搜索具有与第一特征值相似的第二特征值的病例图像 比较结果,并将搜索到的案例图像发送到用户终端。