Contrast-invariant registration of cardiac and renal magnetic resonance perfusion images
    31.
    发明申请
    Contrast-invariant registration of cardiac and renal magnetic resonance perfusion images 有权
    心脏和肾脏磁共振灌注图像的对比不变记录

    公开(公告)号:US20050240099A1

    公开(公告)日:2005-10-27

    申请号:US11078035

    申请日:2005-03-11

    IPC分类号: A61B5/05 A61B5/055

    CPC分类号: A61B5/055

    摘要: A system and method are provided for contrast-invariant registration of images, the system including a processor, an imaging adapter or a communications adapter for receiving an image data sequence, a user interface adapter for selecting a reference frame from the image sequence or cropping a region of interest (ROI) from the reference frame, a tracking unit for tracking the ROI across the image sequence, and an estimation unit for segmenting the ROI in the reference frame or performing an affine registration for the ROI; and the method including receiving an image sequence, selecting a reference frame from the image sequence, cropping a region of interest (ROI) from the reference frame, tracking the ROI across the image sequence, segmenting the ROI in the reference frame, and performing an affine registration for the ROI.

    摘要翻译: 提供了用于对比度不变的图像配准的系统和方法,所述系统包括处理器,成像适配器或用于接收图像数据序列的通信适配器,用于从图像序列中选择参考帧的用户接口适配器或裁剪 来自参考帧的感兴趣区域(ROI),用于跟踪跨越图像序列的ROI的跟踪单元,以及用于在参考帧中分割ROI或对ROI执行仿射注册的估计单元; 并且所述方法包括接收图像序列,从所述图像序列中选择参考帧,从所述参考帧裁剪感兴趣区域(ROI),沿所述图像序列跟踪所述ROI,在所述参考帧中分割所述ROI,以及执行 ROI的仿射注册。

    Editing of pre-segmented images using seeds derived from contours
    34.
    发明授权
    Editing of pre-segmented images using seeds derived from contours 有权
    使用源自轮廓的种子编辑预分割图像

    公开(公告)号:US08131076B2

    公开(公告)日:2012-03-06

    申请号:US12031966

    申请日:2008-02-15

    IPC分类号: G06K9/34

    CPC分类号: G06K9/342

    摘要: A method for processing an object in image data includes the steps of drawing a contour on a pre-segmentation of an object in image data, generating at least one seed point on the pre-segmentation from an intersection of the contour and the pre-segmentation, providing a weighting factor between the seed points and the pre-segmentation, and segmenting the pre-segmentation using the seed points and the weighting factor to generate a new pre-segmentation.

    摘要翻译: 一种用于处理图像数据中的对象的方法包括以下步骤:对图像数据中的对象的预分割绘制轮廓,从轮廓和预分割的交点产生预分割上的至少一个种子点 提供种子点和预分割之间的加权因子,以及使用种子点和加权因子分割预分割以产生新的预分割。

    System for modeling static and dynamic three dimensional anatomical structures by 3-D models
    35.
    发明授权
    System for modeling static and dynamic three dimensional anatomical structures by 3-D models 失效
    三维模型静态和动态三维解剖结构建模系统

    公开(公告)号:US06816607B2

    公开(公告)日:2004-11-09

    申请号:US09858368

    申请日:2001-05-16

    IPC分类号: G06K900

    摘要: The present invention relates to a system of modeling a three dimensional target object which is represented by a plurality of cross-sectional images in order to provide a representative corresponding three dimensional model. The invention selects an initial model from a plurality of available initial models. This selection involves identifying an initial model based on physical similarity to the target object and then superimposing an initial model upon the target object, for each of the plurality of cross-sectional images. A determination is then made of an intersection contour of the initial model and a cross-sectional image of the target object and the determined intersection contour is refined in order to more closely delineate the target object. By sub-sampling points which represent the refined determined intersection contour, the invention obtains a sub-sampled contour dataset. The initial model is then adjusted towards the sub-samples contour to obtain a representative three dimensional model of the target object.

    摘要翻译: 本发明涉及一种由多个横截面图像表示的三维目标对象的建模系统,以便提供代表性的对应的三维模型。 本发明从多个可用的初始模型中选择初始模型。 该选择包括基于与目标对象的物理相似性来识别初始模型,然后针对多个横截面图像中的每一个,将初始模型叠加在目标对象上。 然后确定初始模型和目标对象的横截面图像的交点轮廓,并且对确定的交集轮廓进行细化以便更加紧密地描绘目标对象。 通过对表示精确确定的交集轮廓的子采样点,本发明获得了子采样轮廓数据集。 然后将初始模型调整到子样本轮廓以获得目标对象的代表性三维模型。

    Object tracking technique using polyline contours
    36.
    发明授权
    Object tracking technique using polyline contours 失效
    使用折线轮廓的对象跟踪技术

    公开(公告)号:US06259802B1

    公开(公告)日:2001-07-10

    申请号:US08885041

    申请日:1997-06-30

    IPC分类号: G06K948

    CPC分类号: G06K9/3216 G06T7/246

    摘要: A technique of tracking an object of interest in a sequence of images using active polyline contours. An image processor converts a sequence of images into digital image data related to light intensity at the pixels of each image. A computer stores the digital image data and forms an initial polyline that substantially outlines an edge of the object in a first image. The computer forms input polylines for each of the subsequent images which substantially outline the edge in the corresponding images and are derived from the optimal polyline of each previous such image. The computer processes the digital image data, performing a graph exploration procedure that starts with the initial polyline in the first image and the input polylines in the subsequent images. The graph exploration procedure searches polylines in a predefined search space to find the corresponding optimal polylines. The computer evaluates edge strength of the different polylines with respect to the light intensity of its underlying pixels to obtain corresponding contour costs. The polyline with the smallest contour cost is selected as the optimal contour for each of the images. The set of optimal contours are used to track the object of interest.

    摘要翻译: 使用主动折线轮廓跟踪图像序列中的感兴趣对象的技术。 图像处理器将图像序列转换成与每个图像的像素处的光强相关的数字图像数据。 计算机存储数字图像数据并形成初始折线,其基本上概述第一图像中对象的边缘。 计算机为每个随后的图像形成输入折线,其基本上概述了相应图像中的边缘,并且从每个先前这样的图像的最佳折线导出。 计算机处理数字图像数据,执行从第一图像中的初始折线开始的图形探索过程和随后图像中的输入折线。 图形探索程序在预定义的搜索空间中搜索折线以找到相应的最佳折线。 计算机评估不同折线相对于其底层像素的光强度的边缘强度,以获得相应的轮廓成本。 选择具有最小轮廓成本的折线作为每个图像的最佳轮廓。 最佳轮廓的集合用于跟踪感兴趣的对象。

    LOCALIZATION OF AORTA AND LEFT ATRIUM FROM MAGNETIC RESONANCE IMAGING
    37.
    发明申请
    LOCALIZATION OF AORTA AND LEFT ATRIUM FROM MAGNETIC RESONANCE IMAGING 有权
    磁共振成像中的AORTA和LEFT ATRIUM的定位

    公开(公告)号:US20130096414A1

    公开(公告)日:2013-04-18

    申请号:US13546101

    申请日:2012-07-11

    IPC分类号: A61B5/055

    摘要: The aorta and left atrium are localized from magnetic resonance data. The locations of the aorta and left atrium are detected jointly. The aorta and the left atrium are, at least in part, treated as one object. The detection may be from data representing a two-dimensional region. The two-dimensional region may be determined by first detecting the left ventricle from data representing a volume.

    摘要翻译: 主动脉和左心房由磁共振数据定位。 联合检测主动脉和左心房的位置。 主动脉和左心房至少部分被视为一个对象。 检测可以来自表示二维区域的数据。 可以通过首先从表示体积的数据检测左心室来确定二维区域。

    Method and System for Propagation of Myocardial Infarction from Delayed Enhanced Cardiac Imaging to Cine Magnetic Resonance Imaging Using Hybrid Image Registration
    39.
    发明申请
    Method and System for Propagation of Myocardial Infarction from Delayed Enhanced Cardiac Imaging to Cine Magnetic Resonance Imaging Using Hybrid Image Registration 有权
    使用混合图像配准将心肌梗塞从延迟增强心脏成像传播到电磁共振成像的方法和系统

    公开(公告)号:US20120121154A1

    公开(公告)日:2012-05-17

    申请号:US13296487

    申请日:2011-11-15

    IPC分类号: G06K9/00

    摘要: A method and system for propagation of myocardial infarction from delayed enhanced magnetic resonance imaging (DE-MRI) to cine MRI is disclosed. A reference frame is selected in a cine MRI sequence. Deformation fields are calculated within the cine MRI sequence to register the frames of the cine MRI sequence to the reference frame. A DE-MRI image having an infarction region is registered to the reference frame of the cine MRI sequence. The DE-MRI image may be registered to the infarction region using a hybrid registration algorithm that unifies both intensity and feature points into a single cost function. Infarction information in the DE-MRI image is then propagated cardiac phases of the frames in the cine MRI sequence based on the registration of the DE-MRI image to the reference frame and the plurality of deformation fields calculated within the cine MRI sequence.

    摘要翻译: 公开了一种从延迟增强磁共振成像(DE-MRI)向电磁MRI传播心肌梗死的方法和系统。 在电影MRI序列中选择参考帧。 在电影MRI序列中计算变形场,以将电影MRI序列的帧注册到参考帧。 具有梗塞区域的DE-MRI图像被登记到电影MRI序列的参考帧。 可以使用将强度和特征点统一为单个成本函数的混合配准算法将DE-MRI图像登记到梗塞区域。 DE-MRI图像中的梗死信息然后基于DE-MRI图像的登记到参考帧和在电影MRI序列中计算的多个变形场,在电影MRI序列中的帧的心脏相位传播。

    Method for knowledge based image segmentation using shape models
    40.
    发明授权
    Method for knowledge based image segmentation using shape models 有权
    使用形状模型的基于知识的图像分割方法

    公开(公告)号:US07680312B2

    公开(公告)日:2010-03-16

    申请号:US11429685

    申请日:2006-05-08

    IPC分类号: G06K9/34 G06K9/46

    摘要: A method for segmenting an object of interest from an image of a patient having such object. Each one of a plurality of training shapes is distorted to overlay a reference shape with a parameter Θi being a measure of the amount of distortion required to effect the overlay. A vector of the parameters Θi is obtained for every one of the training shapes through the minimization of a cost function along with an estimate of uncertainty for every one of the obtained vectors of parameters Θi, such uncertainty being quantified as a covariance matrix Σi. A statistical model represented as {circumflex over (f)}H (Θ,Σ) is generated with the sum of kernels having a mean Θi and covariance Σi. The desired object of interest in the image of the patient is identified by positioning of the reference shape on the image and distorting the reference shape to overlay the obtained image with a parameter Θ being a measure of the amount of distortion required to effect the overlay. An uncertainty is quantified as a covariance matrix Σ and an energy function E=Eshape+Eimage is computed to obtain the probability of the current shape in the statistical shape model Eshape(Θ,Σ)=−log({circumflex over (f)}H) and the fit in the image Eimage.

    摘要翻译: 一种用于从具有该对象的患者的图像中分割感兴趣对象的方法。 多个训练形状中的每一个被扭曲以覆盖参考形状,参数Θi是影响覆盖所需的扭曲量的量度。 通过使成本函数的最小化以及对于所获得的参数Θi的每一个的不确定性的估计,对每个训练形状获得参数Θi的向量,这样的不确定性被量化为协方差矩阵Sgr i 。 使用具有平均值Θi和协方差Sgr i的内核的总和来生成表示为{f(f)} H(Θ,&Sgr;)中的回归的统计模型。 通过将参考形状定位在图像上并使参考形状变形以使得所获得的图像重叠,以参数Θ作为影响覆盖所需的失真量的度量来识别期望的患者图像对象。 不确定性被量化为协方差矩阵&Sgr; 并且计算能量函数E = Eshape + Eimage,以获得统计形状模型中的当前形状的概率Eshape(Θ,&Sgr;)= - log({f(f)} H)和图像中的拟合 Eimage。