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    SYSTEM FOR COMPUTERIZED PROCESSING OF CHEST RADIOGRAPHIC IMAGES
    32.
    发明申请
    SYSTEM FOR COMPUTERIZED PROCESSING OF CHEST RADIOGRAPHIC IMAGES 审中-公开
    用于计算机图像处理的系统

    公开(公告)号：WO0028466A9

    公开(公告)日：2000-09-28

    申请号：PCT/US9924007

    申请日：1999-11-05

    Applicant: ARCH DEV CORP ,  DOI KUNIO ,  LI QIANG ,  KATSURAGAWA SHIGEHIKO ,  ISHIDA TAKAYUKI

    Inventor： DOI KUNIO ,  LI QIANG ,  KATSURAGAWA SHIGEHIKO ,  ISHIDA TAKAYUKI

    IPC: A61B6/00 ,  G06T1/00 ,  G06T3/00 ,  G06T5/50 ,  G06T7/60 ,  G06K9/00

    CPC classification number: G06T3/0068 ,  G06T5/50 ,  G06T7/174

    Abstract: A method, system and computer readable medium for computerized processing of chest images including obtaining a digital first image of a chest (S100); producing a second image which is a mirror image (S300) of the first image; performing image warping on one of the first and second images to produce a warped image (S400) which is registered to the other of the first and second images; and subtracting the warped image from the other image to generate a subtraction image (S600). Another embodiment includes obtaining a digital first image of the chest of a subject; detecting ribcage edges on both sides of the lungs in the first chest image; determining average horizontal locations of the left and right ribcage edges at plural vertical locations; fitting the determined average horizontal locations to a straight line to derive a midline; rotating the chest image so that the midline is vertical; and shifting the rotated image to produce a lateral inclination corrected (S200) second image with the midline centered in the lateral inclination corrected image.

    Abstract translation: 一种用于计算机化处理胸部图像的方法，系统和计算机可读介质，包括获得胸部的数字第一图像（S100）; 产生作为第一图像的镜像（S300）的第二图像; 在第一和第二图像之一上执行图像扭曲以产生被注册到第一和第二图像中的另一个的翘曲图像（S400）; 并从另一图像中减去翘曲图像以产生减法图像（S600）。 另一实施例包括获得对象胸部的数字第一图像; 在第一胸部图像中检测肺两侧的肋骨边缘; 确定在多个垂直位置处的左和右胸腔边缘的平均水平位置; 将确定的平均水平位置拟合到直线以导出中线; 旋转胸部图像，使中线垂直; 并移动旋转的图像以产生横向倾斜校正（S200）第二图像，其中心线位于横向倾斜校正图像中。

    METHOD AND SYSTEM FOR THE AUTOMATED TEMPORAL SUBTRACTION OF MEDICAL IMAGES
    34.
    发明申请
    METHOD AND SYSTEM FOR THE AUTOMATED TEMPORAL SUBTRACTION OF MEDICAL IMAGES 审中-公开
    医学图像自动临时放置的方法与系统

    公开(公告)号：WO9942949A9

    公开(公告)日：1999-11-04

    申请号：PCT/US9903282

    申请日：1999-02-22

    Applicant: ARCH DEV CORP

    Inventor： XU XIN-WEI ,  DOI KUNIO

    IPC: G06T5/50 ,  G06T7/20 ,  G06K9/00

    CPC classification number: G06T5/50 ,  A61B6/027 ,  G06T7/254

    Abstract: Method and system for detection of interval change in medical images. Three-dimensional images, such as previous and current section images (10 and 11) in CT scans, are obtained. An anatomic feature, such as lungs, is used to select sections containing lung by a gray-level thresholding technique (13). The section correspondence between the current and previous scans is determined automatically. The initial registration of the corresponding sections in the two scans is achieved by a rotation correction (14) and a cross-correlation (15) technique. A more accurate registration between the corresponding current and previous section images is achieved by local matching (17). A nonlinear warping process (18) which is also based on the cross-correlation technique is applied to the previous image to yield a warped image after the matching. The final subtracted section images (19) were derived by subtracting of the previous section images from the corresponding current section images. Interval changes such as a change in tumor size and a newly developed pleural effusion are enhanced significantly.

    Abstract translation: 用于检测医学图像间隔变化的方法和系统。 获得三维图像，例如CT扫描中的先前和当前部分图像（10和11）。 使用解剖学特征，如肺，通过灰度阈值技术选择含有肺的部位（13）。 自动确定当前扫描和以前扫描之间的部分对应关系。 通过旋转校正（14）和互相关（15）技术来实现两次扫描中相应部分的初始配准。 通过局部匹配（17）实现相应的当前和前一个截面图像之间的更准确的配准。 还将基于互相关技术的非线性翘曲过程（18）应用于先前的图像，以在匹配之后产生翘曲图像。 通过从相应的当前部分图像中减去前一部分图像导出最终减法部分图像（19）。 肿瘤大小变化和新发胸腔积液等间期变化明显增强。

    WAVELET SNAKE TECHNIQUE FOR DISCRIMINATION OF NODULES AND FALSE POSITIVES IN DIGITAL RADIOGRAPHS
    36.
    发明申请
    WAVELET SNAKE TECHNIQUE FOR DISCRIMINATION OF NODULES AND FALSE POSITIVES IN DIGITAL RADIOGRAPHS 审中-公开
    用于歧视数字无线电广播中的节目和虚拟角色的小波收音机技术

    公开(公告)号：WO9905639A9

    公开(公告)日：1999-04-22

    申请号：PCT/US9815278

    申请日：1998-07-24

    Applicant: ARCH DEV CORP

    Inventor： YOSHIDA HIROYUKI ,  KATUSURAGAWA SHIGEHIKO ,  AMIT YALI ,  DOI KUNIO

    IPC: G06K9/64 ,  G06T7/00 ,  G06K9/00

    CPC classification number: G06K9/6206 ,  G06T7/0012

    Abstract: A method and apparatus for discrimination of nodules and false positive in digital chest radiographs, using a wavelet snake technique (1802; 1804; 1806; 1808). The wavelet snake is a deformable contour designed to identify the boundary of a relatively round object (1900). The shape of the snake is determined by a set of wavelet coefficient in a certain range of scales. Portions of the boundary of a nodule are first extracted using a multiscale edge representation. The multiscale edge are then fitted (2000; 1814) by a gradient descent procedure which deforms the shape of a wavelet snake by changing its wavelet coefficients. The degree of overlap between the fitted snake and the multiscale edges is calculated and used as a fit quality indicator for discrimination of nodules and false detection (1816; 1818; 1820).

    Abstract translation: 使用小波蛇技术（1802; 1804; 1806; 1808）在数字胸片中鉴别结节和假阳性的方法和装置。 小波蛇是一种可变形轮廓，用于识别相对圆形物体的边界（1900）。 蛇的形状由一定范围的小波系数确定。 首先使用多尺度边缘表示提取结节边界的部分。 然后通过梯度下降程序将多尺度边缘拟合（2000; 1814），其通过改变其小波系数来变形小波蛇的形状。 计算拟合蛇和多尺度边缘之间的重叠程度，并将其用作辨别结节和错误检测的适合质量指标（1816; 1818; 1820）。

    INDUSTRIAL PROCESS SURVEILLANCE SYSTEM
    37.
    发明申请
    INDUSTRIAL PROCESS SURVEILLANCE SYSTEM 审中-公开
    工业过程监控系统

    公开(公告)号：WO9749011A9

    公开(公告)日：1999-04-15

    申请号：PCT/US9710430

    申请日：1997-06-13

    Applicant: ARCH DEV CORP

    Inventor： GROSS KENNETH C ,  WEGERICH STEPHAN ,  SINGER RALPH M ,  MOTT JACK

    IPC: G05B13/02 ,  G05B9/02 ,  G05B13/04 ,  G05B23/02

    CPC classification number: G05B23/0254 ,  G05B23/0262

    Abstract: A system (10) and method for monitoring an industrial process and/or industrial data source (10). The system (10) includes a time correlation module (20), a training module (30), a system state estimation module (40) and a pattern recognition module (50). The system (10) generating time varying data sources, processing the data to obtain time correlation of the data (20), determining the range of data, determining learned states of normal operation (30) and using these states to generate expected values to identify a current state of the process closest to a learned, normal state (40); generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm (50) upon detecting a deviation from normalcy.

    Abstract translation: 一种用于监测工业过程和/或工业数据源（10）的系统（10）和方法。 系统（10）包括时间相关模块（20），训练模块（30），系统状态估计模块（40）和模式识别模块（50）。 所述系统（10）产生时变数据源，处理数据以获得数据（20）的时间相关性，确定数据范围，确定正常操作的学习状态（30）并使用这些状态来产生期望值以识别 该过程的当前状态最接近学习的正常状态（40）; 生成一组建模数据，并且在检测到与正常偏差之后处理建模数据以识别数据模式并产生报警（50）。

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