公开(公告)号：EP1082694A4

公开(公告)日：2007-08-08

申请号：EP99909494

申请日：1999-02-23

Applicant: ARCH DEV CORP

Inventor： XU XIN-WEI ,  DOI KUNIO

IPC: A61B6/00 ,  G06T1/00 ,  G06T7/00 ,  G06K9/00

CPC classification number: G06T7/0012

Abstract: An automated method and a computer storage medium storing instructions for executing the method, for analysis of image features in lung nodule detection in a digital chest radiographic image, including preprocessing the image to identify candidate nodules in the image (1200); establishing a region of interest (ROI) including a candidate nodule within the ROI (1210); performing image enhancement of the candidate nodule within the ROI (1220); obtaining a histogram of accumulated edge gradients as a function of radial angles within the ROI after performing the image enhancement (1230); and determining whether the candidate nodule is a false positive based on the obtained histogram (1240).

Abstract translation: 一种自动化方法和计算机存储介质，存储用于执行该方法的指令，用于分析数字胸部放射线照相图像中的肺结节检测中的图像特征，包括预处理该图像以识别图像中的候选结节（1200）; 在ROI（1210）内建立包括候选结节的感兴趣区域（ROI）; 执行ROI内的候选结节的图像增强（1220）; 在执行图像增强（1230）之后获得作为ROI内的径向角的函数的累积边缘梯度的直方图; 以及基于所获得的直方图确定候选结节是否为假阳性（1240）。

公开(公告)号：EP0731952A4

公开(公告)日：1997-01-22

申请号：EP95903554

申请日：1994-11-29

Applicant: ARCH DEV CORP

Inventor： GIGER MARYELLEN L ,  DOI KUNIO ,  LU PING ,  HUO ZHIMIN

IPC: A61B6/00 ,  G06K9/00 ,  G06T1/00 ,  G06T7/00 ,  G06K9/38 ,  G06K9/44 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06K9/00127 ,  G06T7/0012

Abstract: A method and system for automated detection and classification of masses in mammograms. This method and system include the performance of iterative, multi-level gray level thresholding (202), followed by lesion extraction (203) and feature extraction techniques (205) for classifying true masses from false-postive masses and malignant masses from benign masses. The method and system provide improvements in the detection of masses including multi-gray-level thresholding (202) of the processed images to increase sensitivity and accurate region growing and feature analysis to increase specificity. Novel improvements in the classification of masses include a cumulative edge gradient orientation histogram analysis relative to the radial angle of the pixels in question; i.e. either around the margin of the mass or within or around the mass in question. The classification of the mass leads to a likelihood malignancy.

公开(公告)号：EP1295244A4

公开(公告)日：2009-06-03

申请号：EP99917300

申请日：1999-04-02

Applicant: ARCH DEV CORP

Inventor： ISHIDA TAKAYUKI ,  KATSURAGAWA SHIGEHIKO ,  DOI KUNIO

IPC: A61B6/00 ,  G06T7/00 ,  G01N20060101 ,  G06K9/00 ,  G06K9/80 ,  G06T1/00 ,  G06T3/00 ,  G06T5/40 ,  G06T7/20 ,  H04N5/325

CPC classification number: G06T7/0016 ,  G06T3/0068 ,  G06T7/254 ,  G06T7/337 ,  G06T2207/30061

Abstract: A method of computerized analysis of temporally sequential digital images, including (a) determining first shift values between pixels of a first digital image and corresponding pixels of a second digital image (440); (b) warping the second digital image based on the first shift values to obtain a first warped image in which spatial locations of pixels are varied in relation to the first shift values (450); (c) determining second shift values between pixels of the first digital image and pixels of the first warped image; and (d) warping the first warped image based on the second shift values to obtain a second warped image (470). Iterative warping enhances image for the first subtraction of the first digital image and the final warped image to produce a difference image (480).

公开(公告)号：EP1025535A4

公开(公告)日：2002-02-13

申请号：EP99933560

申请日：1999-07-21

Applicant: ARCH DEV CORP

Inventor： XU XIN-WEI ,  DOI KUNIO ,  MACMAHON HEBER

IPC: A61B6/00 ,  G06T1/00 ,  G06T7/00 ,  G06K9/00 ,  G06F19/00

CPC classification number: G06T7/0012

Abstract: A method, system and computer readable medium configured for computerized detection of lung abnormalities, including obtaining a standard digital chest image (10) and a soft-tissue digital chest image; generating a first difference image from the standard digital chest image (20) and a second difference image from the soft-tissue digital chest image; identifying candidate abnormalities in the first and second difference images; extracting from the standard digital chest image and the first difference image predetermined first features of each of the candidate abnormalities identified in the first difference image; extracting from the soft-tissue digital chest image and the second difference images predetermined second features of each of the candidate abnormalities identified in the second difference image; analyzing the extracted first features and the extracted second features to identify and eliminate false positive candidate abnormalities respectively corresponding thereto; applying extracted features from remaining candidate abnormalities derived respectively from the first and second difference images and remaining after the elimination of the false positive candidate abnormalities to respective artificial neural networks to eliminate further false positive candidate abnormalities by performing a logical OR operation of the candidate abnormalities derived respectively from the first and second difference images.

公开(公告)号：EP0731956A4

公开(公告)日：1997-04-23

申请号：EP95904081

申请日：1994-11-30

Applicant: ARCH DEV CORP

Inventor： GIGER MARYELLEN L ,  CHEN CHIN-TU ,  ARMATO SAMUEL ,  DOI KUNIO

IPC: G01N23/04 ,  A61B6/00 ,  G06T1/00 ,  G06T3/00 ,  G06T5/00 ,  G06T7/60 ,  G06K9/32 ,  G06K9/38

CPC classification number: G06T7/0012 ,  G06T3/0075 ,  G06T7/12 ,  G06T7/155 ,  G06T7/66 ,  G06T2207/10116 ,  G06T2207/30061

Abstract: A method and system for computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax (10, 12). Techniques include contouring the lung regions in each type of chest image (15, 16), scaling (17) and registration (19) of the contours based on location of lung apices, and superimposition (18) after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lung scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs.

Abstract translation: 一种用于与放射线照相图像，包括来自胸部的X线和放射性核素的图像生成图像数据的放射性核素图像的计算机化登记方法和系统。 技术包括轮廓的肺部区域中的每个类型的胸部图像的，缩放和基于肺顶点的位置，并且叠加的图像的适当的变速后的轮廓的登记。 特定的应用程序，给出了放射性核素肺部扫描与胸片自动注册。 在给定的实施例的方法产生的系统做了空间寄存器和为了与胸部X光的更大的结构细节V / Q功能信息相互关联相关为V / Q数字化的扫描胸片。 最终输出可以是来自图像的每个类型叠加在任何原始图像，或重叠的放射性核素图像数据的，其中含有高活性，走上放射线照相图像胸部所述计算机确定的轮廓。

公开(公告)号：EP1127330A4

公开(公告)日：2003-03-26

申请号：EP99960126

申请日：1999-11-05

Applicant: ARCH DEV CORP

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

IPC: A61B6/00 ,  G06T1/00 ,  G06T3/00 ,  G06T5/50 ,  G06T7/60 ,  G06K9/00 ,  G06F19/00

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生成减法图像（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; 并且移动旋转的图像以产生以横向倾斜校正图像为中心的中线的横向倾斜校正（S200）第二图像。

公开(公告)号：EP0731667A4

公开(公告)日：1997-10-15

申请号：EP95903553

申请日：1994-11-29

Applicant: ARCH DEV CORP

Inventor： GIGER MARYELLEN L ,  DOI KUNIO

IPC: A61B6/00 ,  G06F19/00 ,  G06T7/00 ,  A61B5/103

CPC classification number: G06T7/0012 ,  A61B6/4042 ,  A61B6/482 ,  A61B6/505 ,  A61B6/583 ,  G06T2207/10116 ,  G06T2207/30008 ,  G06T2207/30012

Abstract: A computerized method and system for the radiographic analysis of bone structure. Techniques include texture analysis for use in quantitating the bone structure and risk of fracture. Texture analysis of the bone structure incorporates directionality information, for example, in terms of the angular dependence of the RMS variation and first moment of the power spectrum of a ROI in a bony region. The system includes using dual energy imaging to obtain measures of both mass and bone structure with one exam. Specific applications are given for the analysis of regions within the vertebral bodies on conventional spine radiographs. Techniques include novel features that characterize the power spectrum of the bone structure and allow extraction of directionality features with which to characterize the spatial distribution and thickness of the bone trabeculae. These features are then merged using artifical neural networks in order to yield a likelihood of risk of future fracture.

公开(公告)号：JPH10171910A

公开(公告)日：1998-06-26

申请号：JP30713097

申请日：1997-11-10

Applicant: ARCH DEV CORP

Inventor： DOI KUNIO ,  ISHIDA TAKAYUKI ,  KATSURAGAWA SHIGEHIKO

IPC: A61B5/00 ,  G06F15/18 ,  G06N3/00 ,  G06Q50/00 ,  G06T1/00 ,  G06T7/00 ,  G06F19/00

Abstract: PROBLEM TO BE SOLVED: To efficiently detect an abnormality using an artificial neural network by providing a 2nd neural network means for outputting 2nd signal data based on 1st signal data, and a decision means for outputting a diagnosis result based on the 2nd signal data, etc. SOLUTION: This system is composed of an extracting means for extracting part data from picture data, a 1st neural network means for outputting the 1st signal data based on the extracted part data, the 2nd neural network means for outputting the 2nd signal data based on the 1st signal data, and the decision means for outputting the diagnosis result based on the 2nd signal data. Then, the part data is extracted from the picture data, and the 1st signal data is outputted from the 1st neural network based on this part data. The 2nd signal data is outputted from the 2nd neural network based on this 1st signal data, and the diagnosis result is outputted based on this data.

公开(公告)号：JPH10155746A

公开(公告)日：1998-06-16

申请号：JP31233797

申请日：1997-11-13

Applicant: ARCH DEV CORP

Inventor： ROGER ENGELMAN ,  KENNETH R HOFFMAN ,  HABA MCMAHON ,  DOI KUNIO

IPC: A61B5/00 ,  A61B6/00 ,  G06F19/00 ,  G06T19/00 ,  H04N5/325

Abstract: PROBLEM TO BE SOLVED: To efficiently display a number of images of a specimen with a simple operation by obtaining diagnosis information concerning a medical image to display the medical image in a first display area of a display screen and an image corresponding to the diagnosis information in a second display area. SOLUTION: The name of a patient linked to a medical image loaded from a memory/archive and an identification number(ID) of the patient or an image itself are displayed in a patient information area 33. Three types of image sets comprising differential images, previous images used for the generation thereof and current images are simultaneously displayed in a main image observation area 31 limited within a screen of a display device. A plurality of buttons designed in the differential image are arranged in a computer aided diagnosis/ image selection area 32 and can be used by a user to freely switch the current images, the previous images and the results of the CAD in the main image observation area 31. This also enables checking of a plurality of images to be read at a time.

公开(公告)号：JP2005176402A

公开(公告)日：2005-06-30

申请号：JP2005019694

申请日：2005-01-27

Applicant: Arch Dev Corp ,  アーチ・デベロップメント・コーポレーション

Inventor： KANO AKIKO ,  DOI KUNIO

IPC: A61B6/00 ,  G06Q50/00 ,  G06T1/00 ,  G06T3/00 ,  G06T5/50 ,  G06T7/00 ,  H04N5/325

CPC classification number: G06T3/0081 ,  G06T5/50 ,  G06T2207/20224 ,  Y10S128/922

Abstract: PROBLEM TO BE SOLVED: To provide a computerized method and apparatus for improving diagnostic precision using intensified images for detecting interval changes between temporally sequential digitized medical images.
SOLUTION: A pair of images are digitized (steps 10, 20) and then subjected to image registration including non-linear warping of one of the images so that corresponding locations in the two images are aligned with each other (step 40). Subsequent to image registration, a subtraction process is performed on the warped image and the other image (step 50). In this manner, slight opacities which are only present in the later image, may be detected in a subtraction image.
COPYRIGHT: (C)2005,JPO&NCIPI

Abstract translation: 要解决的问题：提供一种使用强化图像提高诊断精度的计算机化方法和装置，用于检测时间上顺序的数字化医学图像之间的间隔变化。 解决方案：一对图像被数字化（步骤10,20），然后进行图像配准，包括其中一个图像的非线性翘曲，使得两个图像中的相应位置彼此对准（步骤40） 。 在图像配准之后，对翘曲图像和其他图像执行减法处理（步骤50）。 以这种方式，可以在减法图像中检测到仅存在于稍后图像中的轻微不透明度。 版权所有（C）2005，JPO＆NCIPI