Semi-automatic Segmentation of Cardiac Ultrasound Images using a Dynamic Model of the Left Ventricle
    1.
    发明申请
    Semi-automatic Segmentation of Cardiac Ultrasound Images using a Dynamic Model of the Left Ventricle 审中-公开
    使用左心室动态模型对心脏超声图像进行半自动分割

    公开(公告)号:US20090161926A1

    公开(公告)日:2009-06-25

    申请号:US12028884

    申请日:2008-02-11

    IPC分类号: G06K9/00 G06K9/34

    摘要: A method for segmenting a sequence of images includes developing an autoregressive model using training data including segmented images of a same type as the sequence of images. The sequence of images showing a progression of a subject through a cycle is acquired. At least two images from the sequence of images are identified. A region of interest is manually segmented from the identified images. The manually segmented images are parameterized. The autoregressive model is adapted to the parameterized segmented images. The autoregressive model is used to perform segmentation on the region of interest for a plurality of images of the sequence of images.

    摘要翻译: 用于分割图像序列的方法包括使用包括与图像序列相同类型的分割图像的训练数据来开发自回归模型。 获取通过循环显示受检者进展的图像序列。 识别来自图像序列的至少两个图像。 感兴趣的区域是从识别的图像手动分割的。 手动分割的图像被参数化。 自回归模型适用于参数化分割图像。 自回归模型用于对图像序列的多个图像在感兴趣区域上进行分割。

    Sparse volume segmentation for 3D scans
    2.
    发明授权
    Sparse volume segmentation for 3D scans 有权
    用于3D扫描的稀疏音量分割

    公开(公告)号:US08073252B2

    公开(公告)日:2011-12-06

    申请号:US11754476

    申请日:2007-05-29

    IPC分类号: G06K9/34

    摘要: A computer readable medium is provided embodying instructions executable by a processor to perform a method for sparse volume segmentation for 3D scan of a target. The method including learning prior knowledge, providing volume data comprising the target, selecting a plurality of key contours of the image of the target, building a 3D spare model of the image of the target given the plurality of key contours, segmenting the image of the target given the 3D sparse model, and outputting a segmentation of the image of the target.

    摘要翻译: 提供了一种计算机可读介质,其包含可由处理器执行的指令,以执行用于目标的3D扫描的稀疏卷分割的方法。 该方法包括学习预先知识,提供包括目标的体数据,选择目标图像的多个关键轮廓,构建给定多个关键轮廓的目标图像的3D备用模型,分割图像的图像 给定3D稀疏模型的目标,并输出目标图像的分割。

    Sparse Volume Segmentation for 3D Scans
    3.
    发明申请
    Sparse Volume Segmentation for 3D Scans 有权
    用于3D扫描的稀疏体积分割

    公开(公告)号:US20110123095A1

    公开(公告)日:2011-05-26

    申请号:US11754476

    申请日:2007-05-29

    IPC分类号: G06K9/00

    摘要: A computer readable medium is provided embodying instructions executable by a processor to perform a method for sparse volume segmentation for 3D scan of a target. The method including learning prior knowledge, providing volume data comprising the target, selecting a plurality of key contours of the image of the target, building a 3D spare model of the image of the target given the plurality of key contours, segmenting the image of the target given the 3D sparse model, and outputting a segmentation of the image of the target.

    摘要翻译: 提供了一种计算机可读介质,其包含可由处理器执行的指令,以执行用于目标的3D扫描的稀疏卷分割的方法。 该方法包括学习预先知识,提供包括目标的体数据,选择目标图像的多个关键轮廓,构建给定多个关键轮廓的目标图像的3D备用模型,分割图像的图像 给定3D稀疏模型的目标,并输出目标图像的分割。

    Automatic organ detection using machine learning and classification algorithms
    4.
    发明授权
    Automatic organ detection using machine learning and classification algorithms 有权
    自动器官检测采用机器学习和分类算法

    公开(公告)号:US07894653B2

    公开(公告)日:2011-02-22

    申请号:US11747961

    申请日:2007-05-14

    IPC分类号: G06K9/00

    摘要: A method and apparatus of visually depicting an organ, having the steps of choosing a predefined set features for analysis, the predefined set of features having distinguishing weak learners for an algorithm, wherein the predefined set of features and the weak learners chosen distinguish features of the organ desired to be represented, developing a strong classifier for the algorithm for the organ desired to be represented based upon the weak learners for the organ, one of conducing a body scan to produce a body scan data set and obtaining a body scan data set of information for a patient, applying the strong classifier and the algorithm to the body scan data set to develop a result of a representation of the organ and outputting the result of the step of applying of the strong classifier and the algorithm to the body scan data set to represent the organ.

    摘要翻译: 一种视觉描绘器官的方法和装置,具有选择用于分析的预定义集合特征的步骤,所述预定义特征集合具有针对算法的区别弱学习者,其中所选择的特定组和弱学习者选择区分特征的特征 期望被表示的器官,为基于用于器官的弱学习者所希望表示的器官的算法开发强分类器,其中一个是进行身体扫描以产生身体扫描数据集并且获得身体扫描数据集 用于患者的信息,将强分类器和算法应用于身体扫描数据集以产生器官表示的结果,并将强分类器和算法的步骤的结果输出到身体扫描数据集 代表器官。

    Particle filter based vessel segmentation
    5.
    发明申请
    Particle filter based vessel segmentation 审中-公开
    基于粒子滤波器的血管分割

    公开(公告)号:US20060251325A1

    公开(公告)日:2006-11-09

    申请号:US11265586

    申请日:2005-11-02

    IPC分类号: G06K9/34

    摘要: A system and method for particle filter based vessel segmentation are provided, the system including a processor, a Particle Filter unit in signal communication with the processor, and a Vessel Segmentation unit in signal communication with the processor; and the method including receiving image data for a vessel, initializing the vessel, modeling successive planes of the vessel as unknown states of a sequential process, and using a Particle Filter with a Monte Carlo sampling rule to propagate a plurality of segmentation hypotheses in parallel.

    摘要翻译: 提供了一种用于基于粒子滤波器的血管分割的系统和方法,该系统包括处理器,与处理器进行信号通信的粒子滤波器单元和与处理器进行信号通信的血管分割单元; 并且所述方法包括接收血管的图像数据,初始化血管,将血管的连续平面建模为顺序过程的未知状态,以及使用具有蒙特卡洛采样规则的粒子滤波器并行地传播多个分割假设。

    Tree structure based 2D to 3D registration
    6.
    发明申请
    Tree structure based 2D to 3D registration 有权
    基于树结构的2D到3D注册

    公开(公告)号:US20060188139A1

    公开(公告)日:2006-08-24

    申请号:US11303564

    申请日:2005-12-16

    IPC分类号: G06K9/00

    摘要: A system and method for tree structure based two-dimensional to three-dimensional registration are provided for receiving three-dimensional (3D) data indicative of vessels, segmenting the 3D data with a vessel tree, simulating two-dimensional (2D) data responsive to the segmented 3D data to form a simulated 2D image, receiving 2D data indicative of vessels, segmenting the received 2D data with a vessel tree, finding a distance transform of the segmented 2D data to form a 2D distance map image, considering a set of poses as state vectors with the corresponding probability computed using the similarity measure computation, re-sampling the pose vector to find a set of most probable poses and considering them as hypothesized poses, recomputing the projection and re-evaluating the probability of the hypothesized poses and updating the state vector until the optimal pose is found.

    摘要翻译: 提供了一种用于基于树结构的二维至三维配准的系统和方法,用于接收指示血管的三维(3D)数据,用血管树分割3D数据,模拟二维(2D)数据,响应于 分割的3D数据以形成模拟2D图像,接收指示血管的2D数据,用血管树分割接收的2D数据,找到分割的2D数据的距离变换以形成2D距离图图像,考虑一组姿势 作为具有使用相似度测量计算计算的相应概率的状态向量,重新采样姿态向量以找到一组最可能的姿势并将其视为假设姿势,重新计算投影并重新估计假设姿势的概率和更新 状态矢量,直到找到最佳姿势。

    AUTOMATIC ORGAN DETECTION USING MACHINE LEARNING AND CLASSIFICATION ALGORITHMS
    7.
    发明申请
    AUTOMATIC ORGAN DETECTION USING MACHINE LEARNING AND CLASSIFICATION ALGORITHMS 有权
    使用机器学习和分类算法的自动机器检测

    公开(公告)号:US20080154565A1

    公开(公告)日:2008-06-26

    申请号:US11747961

    申请日:2007-05-14

    IPC分类号: G06G7/60

    摘要: A method and apparatus of visually depicting an organ, having the steps of choosing a predefined set features for analysis, the predefined set of features having distinguishing weak learners for an algorithm, wherein the predefined set of features and the weak learners chosen distinguish features of the organ desired to be represented, developing a strong classifier for the algorithm for the organ desired to be represented based upon the weak learners for the organ, one of conducing a body scan to produce a body scan data set and obtaining a body scan data set of information for a patient, applying the strong classifier and the algorithm to the body scan data set to develop a result of a representation of the organ and outputting the result of the step of applying of the strong classifier and the algorithm to the body scan data set to represent the organ.

    摘要翻译: 一种视觉描绘器官的方法和装置,具有选择用于分析的预定义集合特征的步骤,所述预定义特征集合具有针对算法的区别弱学习者,其中所选择的特定组和弱学习者选择区分特征的特征 期望被表示的器官,为基于用于器官的弱学习者所希望表示的器官的算法开发强分类器,其中一个是进行身体扫描以产生身体扫描数据集并且获得身体扫描数据集 用于患者的信息,将强分类器和算法应用于身体扫描数据集以产生器官表示的结果,并将强分类器和算法的步骤的结果输出到身体扫描数据集 代表器官。

    Method and apparatus for generating a 2D image having pixels corresponding to voxels of a 3D image
    8.
    发明申请
    Method and apparatus for generating a 2D image having pixels corresponding to voxels of a 3D image 有权
    用于生成具有与3D图像的体素对应的像素的2D图像的方法和装置

    公开(公告)号:US20060251307A1

    公开(公告)日:2006-11-09

    申请号:US11398210

    申请日:2006-04-04

    IPC分类号: G06K9/00

    CPC分类号: G06T11/008 G06T15/08

    摘要: Disclosed is a method and apparatus for generating a two dimensional (2D) image of a structure (e.g., an organ) that has at least one pixel corresponding to at least one voxel of a three dimensional (3D) image of the structure. First, the surface of the structure in the 3D image is modeled by a geometrical volume such as an ellipsoid. Next, normal maximum intensity projection (MIP) rays are cast (i.e., projected) for voxels of the geometrical volume. The 2D image is then generated using the rays. The 2D image has at least one pixel that corresponds to at least one voxel of the 3D image.

    摘要翻译: 公开了一种用于生成具有与该结构的三维(3D)图像的至少一个体素相对应的至少一个像素的结构(例如,器官)的二维(2D)图像的方法和装置。 首先,3D图像中的结构的表面由诸如椭圆体的几何体积建模。 接下来,对于几何体积的体素,投射(即投影)正常的最大强度投影(MIP)射线。 然后使用光线生成2D图像。 2D图像具有对应于3D图像的至少一个体素的至少一个像素。

    System and method for vascular segmentation by Monte-Carlo sampling
    9.
    发明申请
    System and method for vascular segmentation by Monte-Carlo sampling 有权
    通过蒙特卡洛抽样进行血管分割的系统和方法

    公开(公告)号:US20060239541A1

    公开(公告)日:2006-10-26

    申请号:US11384894

    申请日:2006-03-20

    IPC分类号: G06K9/00 G06K9/34 G06T15/00

    摘要: A method of segmenting tubular structures in digital images includes selecting a point in an image of a tubular object to be segmented, defining an initial state of the selected point, initializing measurement weights, a conditional probability distribution and a prior probability distribution of a feature space of the initial state, sampling the feature space from the prior probability distribution, estimating a posterior probability distribution by summing sample measurements weighted by the measurement weights, and segmenting a cross section of the tubular object from the posterior probability distribution.

    摘要翻译: 在数字图像中分割管状结构的方法包括:选择要分割的管状物体的图像中的点,定义所选点的初始状态,初始化测量权重,条件概率分布和特征空间的先验概率分布 的初始状态,从先验概率分布中抽取特征空间,通过对由测量权重加权的样本测量求和来估计后验概率分布,以及从后验概率分布中分割管状对象的横截面。

    Method for detection and tracking of deformable objects using adaptive time-varying autoregressive model
    10.
    发明申请
    Method for detection and tracking of deformable objects using adaptive time-varying autoregressive model 审中-公开
    使用自适应时变自回归模型检测和跟踪可变形物体的方法

    公开(公告)号:US20070098221A1

    公开(公告)日:2007-05-03

    申请号:US11511527

    申请日:2006-08-28

    IPC分类号: G06K9/00 G06K9/34 G06K9/62

    摘要: A method is provided for segmenting a moving object immersed in a background, comprising: obtaining a time-varying autoregressive model of prior motion of the object to predict future motion of the object; predicting a subsequent contour of the object from the background using the obtaining time-varying autoregressive model comprising using the obtained time-varying autoregressive model to initialize and/or constrain segmentation of the object from the background, and segmenting the object using the predicted subsequent contour and updating the autoregressive model while tracking of the segmented object.

    摘要翻译: 提供了一种用于分割浸在背景中的运动物体的方法,包括:获得物体的先前运动的时变自回归模型,以预测物体的未来运动; 使用获得的时变自回归模型从背景预测对象的后续轮廓,包括使用所获得的时变自回归模型来初始化和/或约束来自背景的对象的分割,以及使用预测的后续轮廓来分割对象 并在跟踪分段对象的同时更新自回归模型。