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    Reducing false positives for automatic computerized detection of objects
    31.
    发明申请
    Reducing false positives for automatic computerized detection of objects 有权
    减少自动计算机检测物体的误报

    公开(公告)号：US20070058870A1

    公开(公告)日：2007-03-15

    申请号：US11516213

    申请日：2006-09-06

    申请人： Jianming Liang ,  Zhiyun Xue ,  Marcos Salganicoff ,  Matthias Wolf

    发明人： Jianming Liang ,  Zhiyun Xue ,  Marcos Salganicoff ,  Matthias Wolf

    IPC分类号： G06K9/46 ,  G06K9/34

    CPC分类号： G06T7/0012

    摘要： A computer-implemented method for identifying an object of interest includes providing input data including an image and a candidate for the object of interest in the image, extracting a boundary of the candidate, and extracting a segment of a region of interest containing the candidate. The method further includes determining a plurality of features of an extracted segment of the region of interest containing the candidate, and outputting the object of interest, wherein the object of interest is characterized by the plurality of features, wherein the object of interest and the plurality of features are stored as computer-readable code.

    摘要翻译： 用于识别感兴趣对象的计算机实现的方法包括提供包括图像中的图像和感兴趣对象的候选者的输入数据，提取候选者的边界，以及提取包含候选的感兴趣区域的片段。 该方法还包括确定包含该候选者的所述感兴趣区域的提取段的多个特征，并输出所述感兴趣对象，其中所述感兴趣对象由所述多个特征表征，其中所述感兴趣对象和所述多个特征 功能存储为计算机可读代码。

    Method and apparatus for securely transmitting and authenticating biometric data over a network
    32.
    发明授权
    Method and apparatus for securely transmitting and authenticating biometric data over a network 有权
    用于通过网络安全地传输和认证生物特征数据的方法和装置

    公开(公告)号：US06332193B1

    公开(公告)日：2001-12-18

    申请号：US09232538

    申请日：1999-01-18

    申请人： Randal Glass ,  Marcos Salganicoff ,  Ulf Cahn von Seelen

    发明人： Randal Glass ,  Marcos Salganicoff ,  Ulf Cahn von Seelen

    IPC分类号： H04K100

    CPC分类号： H04L63/0807 ,  G06F21/32 ,  G06F2221/2129 ,  G06F2221/2137 ,  G06Q20/341 ,  G06Q20/40145 ,  G07C9/00158 ,  G07F7/1008 ,  H04L9/3231 ,  H04L9/3234 ,  H04L9/3247 ,  H04L63/0823 ,  H04L63/0861 ,  H04L63/12 ,  H04L2209/56 ,  H04L2209/608 ,  H04L2209/805 ,  H04L2463/102

    摘要： A method and apparatus for collecting and securely transmitting biometric data over a network contains a sensor, preferably a camera, for collecting biometric data and code generating hardware and software. The camera data is digitized and a unique code which is a function of the digitized camera data, a secret key and a transaction token is attached to the digital file. The code may identify the sensor which acquired the biometric information, a time at which the biometric information was acquired, or a time interval during which the data is considered to be valid, and a unique transaction code. The data and code are transmitted over a network to a server which authenticates that the data has not been altered by recomputing the code using its own knowledge of the secret key and transaction token needed to generate the code. If the data is authentic the server then computes a biometric template using the data. This biometric template is then compared to a previously defined biometric template to identify the user and give the user access to a secured resource. The system can be used for online banking and Internet commerce transactions.

    摘要翻译： 用于通过网络收集和安全地传输生物测定数据的方法和装置包含用于收集生物特征数据和代码生成硬件和软件的传感器，优选地是相机。 相机数据被数字化，并且作为数字化相机数据，秘密密钥和交易令牌的函数的唯一代码被附加到数字文件。 代码可以识别获取生物特征信息的传感器，获取生物特征信息的时间，或数据被认为是有效的时间间隔，以及唯一的交易代码。 数据和代码通过网络传输到服务器，该服务器通过使用其自己的秘密密钥知识和生成代码所需的事务令牌来重新计算代码来认证数据没有被改变。 如果数据是真实的，则服务器然后使用数据计算生物特征模板。 然后将该生物特征模板与先前定义的生物特征模板进行比较，以识别用户并给予用户对安全资源的访问。 该系统可用于网上银行和互联网商务交易。

    Method and system for polyp segmentation for 3D computed tomography colonography
    35.
    发明授权
    Method and system for polyp segmentation for 3D computed tomography colonography 有权
    用于3D计算机断层扫描结构的息肉分割方法和系统

    公开(公告)号：US08184888B2

    公开(公告)日：2012-05-22

    申请号：US12231772

    申请日：2008-09-05

    申请人： Le Lu ,  Adrian Barbu ,  Matthias Wolf ,  Sarang Lakare ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    发明人： Le Lu ,  Adrian Barbu ,  Matthias Wolf ,  Sarang Lakare ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    IPC分类号： G06K9/46

    CPC分类号： G06T7/0012 ,  G06T7/11 ,  G06T7/143 ,  G06T2207/10081 ,  G06T2207/20076 ,  G06T2207/30032

    摘要： A method and system for polyp segmentation in computed tomography colonogrphy (CTC) volumes is disclosed. The polyp segmentation method utilizes a three-staged probabilistic binary classification approach for automatically segmenting polyp voxels from surrounding tissue in CTC volumes. Based on an input initial polyp position, a polyp tip is detected in a CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary.

    摘要翻译： 公开了一种计算机断层扫描（CTC）体积中息肉分割的方法和系统。 息肉分割方法采用三阶段概率二分类方法，自动分割CTC体积周围组织的息肉体素。 基于输入的初始息肉位置，使用训练有素的3D点检测器在CTC体积中检测息肉末端。 然后将局部极坐标系拟合到CTC体积中的结肠表面，其中原点在检测到的息肉末端。 使用训练有素的3D框，在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。 基于检测到的息肉内部体素和息肉外部体素，通过使用训练有素的分类器进行升压1D曲线解析，在局部极坐标系的每个轴上检测边界体素。 这导致分段息肉边界。

    User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography
    37.
    发明授权
    User interface for polyp annotation, segmentation, and measurement in 3D computed tomography colonography 有权
    用于三维计算机断层扫描结构中息肉注解，分割和测量的用户界面

    公开(公告)号：US08126244B2

    公开(公告)日：2012-02-28

    申请号：US12231771

    申请日：2008-09-05

    申请人： Le Lu ,  Adrian Barbu ,  Matthias Wolf ,  Sarang Lakare ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    发明人： Le Lu ,  Adrian Barbu ,  Matthias Wolf ,  Sarang Lakare ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    IPC分类号： G06K9/34

    CPC分类号： G16H40/63 ,  G06F19/00 ,  G06T7/0012 ,  G06T7/12 ,  G06T2200/24 ,  G06T2207/10072 ,  G06T2207/20092 ,  G06T2207/30032

    摘要： A method and system for providing a user interface for polyp annotation, segmentation, and measurement in computer tomography colonography (CTC) volumes is disclosed. The interface receives an initial polyp position in a CTC volume, and automatically segments the polyp based on the initial polyp position. In order to segment the polyp, a polyp tip is detected in the CTC volume using a trained 3D point detector. A local polar coordinate system is then fit to the colon surface in the CTC volume with the origin at the detected polyp tip. Polyp interior voxels and polyp exterior voxels are detected along each axis of the local polar coordinate system using a trained 3D box. A boundary voxel is detected on each axis of the local polar coordinate system based on the detected polyp interior voxels and polyp exterior voxels by boosted 1D curve parsing using a trained classifier. This results in a segmented polyp boundary. The segmented polyp is displayed in the user interface, and a user can modify the segmented polyp boundary using the interface. The interface can measure the size of the segmented polyp in three dimensions. The user can also use the interface for polyp annotation in CTC volumes.

    摘要翻译： 公开了一种用于在计算机断层造影（CTC）体积中提供用于息肉注释，分割和测量的用户界面的方法和系统。 界面在CTC体积中接收初始息肉位置，并根据初始息肉位置自动分段息肉。 为了分割息肉，使用训练有素的3D点检测器在CTC体积中检测息肉末端。 然后将局部极坐标系拟合到CTC体积中的结肠表面，其中原点在检测到的息肉末端。 使用训练有素的3D框，在局部极坐标系的每个轴上检测Polyp内部体素和息肉外部体素。 基于检测到的息肉内部体素和息肉外部体素，通过使用训练有素的分类器进行升压1D曲线解析，在局部极坐标系的每个轴上检测边界体素。 这导致分段息肉边界。 分段息肉显示在用户界面中，用户可以使用界面修改分段息肉边界。 界面可以在三维中测量分段息肉的大小。 用户还可以在CTC卷中使用界面进行息肉注释。

    Method and system for detection and registration of 3D objects using incremental parameter learning
    38.
    发明授权
    Method and system for detection and registration of 3D objects using incremental parameter learning 有权
    使用增量参数学习检测和注册3D对象的方法和系统

    公开(公告)号：US08068654B2

    公开(公告)日：2011-11-29

    申请号：US12012386

    申请日：2008-02-01

    申请人： Adrian Barbu ,  Le Lu ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    发明人： Adrian Barbu ,  Le Lu ,  Luca Bogoni ,  Marcos Salganicoff ,  Dorin Comaniciu

    IPC分类号： G06K9/00 ,  G06T15/00

    CPC分类号： G06K9/32 ,  G06K9/00201 ,  G06K9/6256 ,  G06K2209/051

    摘要： A method and system for detecting 3D objects in images is disclosed. In particular, a method and system for Ileo-Cecal Valve detection in 3D computed tomography (CT) images using incremental parameter learning and ICV specific prior learning is disclosed. First, second, and third classifiers are sequentially trained to detect candidates for position, scale, and orientation parameters of a box that bounds an object in 3D image. In the training of each sequential classifier, new training samples are generated by scanning the object's configuration parameters in the current learning projected subspace (position, scale, orientation), based on detected candidates resulting from the previous training step. This allows simultaneous detection and registration of a 3D object with full 9 degrees of freedom. ICV specific prior learning can be used to detect candidate voxels for an orifice of the ICV and to detect initial ICV box candidates using a constrained orientation alignment at each candidate voxel.

    摘要翻译： 公开了一种用于检测图像中的3D物体的方法和系统。 特别地，公开了使用增量参数学习和ICV特有的先前学习的3D计算机断层摄影（CT）图像中Ileo-Cecal Valve检测的方法和系统。 顺序训练第一，第二和第三分类器以检测在3D图像中界定对象的框的位置，缩放和取向参数的候选。 在每个顺序分类器的训练中，基于从先前的训练步骤得到的检测到的候选，通过在当前学习投影子空间（位置，比例，方向）中扫描对象的配置参数来生成新的训练样本。 这允许同时检测和注册具有全9自由度的3D对象。 ICV具体的先验学习可用于检测ICV孔口的候选体素，并使用每个候选体素上的约束取向对齐来检测初始ICV盒候选。

    System and method for computer aided detection via asymmetric cascade of sparse linear classifiers
    40.
    发明授权
    System and method for computer aided detection via asymmetric cascade of sparse linear classifiers 有权
    通过稀疏线性分类器的不对称级联进行计算机辅助检测的系统和方法

    公开(公告)号：US07756313B2

    公开(公告)日：2010-07-13

    申请号：US11592869

    申请日：2006-11-03

    申请人： Jinbo Bi ,  Senthil Periaswamy ,  Kazunori Okada ,  Toshiro Kubota ,  Glenn Fung ,  Marcos Salganicoff ,  R. Bharat Rao

    发明人： Jinbo Bi ,  Senthil Periaswamy ,  Kazunori Okada ,  Toshiro Kubota ,  Glenn Fung ,  Marcos Salganicoff ,  R. Bharat Rao

    IPC分类号： G06K9/00

    CPC分类号： G06K9/6256 ,  G06K9/6282

    摘要： A method for computer aided detection of anatomical abnormalities in medical images includes providing a plurality of abnormality candidates and features of said abnormality candidates, and classifying said abnormality candidates as true positives or false positives using a hierarchical cascade of linear classifiers of the form sign(wTx+b), wherein x is a feature vector, w is a weighting vector and b is a model parameter, wherein different weights are used to penalize false negatives and false positives, and wherein more complex features are used for each successive stage of said cascade of classifiers.

    摘要翻译： 一种用于计算机辅助检测医学图像中的解剖异常的方法，包括提供所述异常候选的多个异常候选和特征，并且使用形式符号的线性分类器（wTx）的分级级联将所述异常候选分类为真正的肯定或假阳性 + b），其中x是特征向量，w是加权向量，b是模型参数，其中使用不同权重来惩罚假否定和假阳性，并且其中对于级联的每个连续阶段使用更复杂的特征 的分类器。