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1. 发明公开

EP1025535A1 COMPUTERIZED DETECTION OF LUNG NODULES USING ENERGY-SUBTRACTED SOFT-TISSUE AND STANDARD CHEST IMAGES 审中-公开
标题翻译： LUNGENNODULEN计算机化检测中减去软组织和乳腺标准
公开(公告)号：EP1025535A1
公开(公告)日：2000-08-09
申请号：EP99933560.7
申请日：1999-07-21
申请人： Arch Development Corporation
发明人： XU, Xin-Wei , DOI, Kunio , MACMAHON, Heber
IPC分类号： G06K9/00
CPC分类号： G06T7/0012
摘要： 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.

2. 发明公开

EP0993269A2 METHODS FOR IMPROVING THE ACCURACY IN DIFFERENTIAL DIAGNOSIS ON RADIOLOGIC EXAMINATIONS 失效
标题翻译：方法以提高在放射性检查鉴别诊断准确性
公开(公告)号：EP0993269A2
公开(公告)日：2000-04-19
申请号：EP98936974.9
申请日：1998-07-24
申请人： Arch Development Corporation
发明人： NISHIKAWA, Robert, M. , JIANG, Yulei , ASHIZAWA, Kazuto , DOI, Kunio
IPC分类号： A61B5/05
CPC分类号： G06T7/0012 , G06F19/00 , Y10S128/925
摘要： A computer-aided method for detecting, classifying, and displaying candidate abnormalities, such as microcalcifications and interstitial lung disease in digitized medical images, such as mammograms and chest radiographs, a computer programmed to implement the method, and a data structure for storing required parameters, wherein in the classifying method candidate abnormalities in a digitized medical image are located, regions are generated around one or more of the located candidate abnormalities, features are extracted from at least one of the located candidate abnormalities within the region and from the region itself, the extracted features are applied to a classification technique, such as an artificial neural network (ANN) to produce a classification result (i.e., probability of malignancy in the form of a number and a bar graph), and the classification result is displayed along with the digitized medical image annotated with the region and the candidate abnormalities within the region. In the detecting method candidate abnormalities in each of a plurality of digitized medical images are located, regions around one or more of the located candidate abnormalities in each of a plurality of digitized medical images are generated, the plurality of digitized medical images annotated with respective regions and candidate abnormalities within the regions are displayed, and a first indicator (e.g., blue arrow) is superimposed over candidate abnormalities comprising of clusters and a second indicator (e.g., red arrow) is superimposed over candidate abnormalities comprising of masses. In a user modification mode, during classification, a user modifies the located candidate abnormalities, the determined regions, and/or the extracted features, so as to modify the extracted features applied to the classification technique and the displayed results, and, during detection, a user modifies the located candidate abnormalities, the determined regions, and the extracted features, so as to modify the displayed results.

3. 发明授权

EP0731667B1 COMPUTERIZED RADIOGRAPHIC ANALYSIS OF BONE 失效
标题翻译：计算机辅助骨组织的X射线分析
公开(公告)号：EP0731667B1
公开(公告)日：2003-05-07
申请号：EP95903553.6
申请日：1994-11-29
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , DOI, Kunio
IPC分类号： A61B5/103 , G06T7/00
CPC分类号： G06T7/0012 , A61B6/4042 , A61B6/482 , A61B6/505 , A61B6/583 , G06T2207/10116 , G06T2207/30008 , G06T2207/30012

4. 发明授权

EP0731952B1 AUTOMATED METHOD AND SYSTEM FOR IMPROVED COMPUTERIZED DETECTION AND CLASSIFICATION OF MASSES IN MAMMOGRAMS 失效
标题翻译： FOR乳房X线照片改进计算机化的检测和分类大众的自动方法和系统
公开(公告)号：EP0731952B1
公开(公告)日：2003-05-02
申请号：EP95903554.4
申请日：1994-11-29
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , DOI, Kunio , LU, Ping , HUO, Zhimin
IPC分类号： G06T5/00 , G06K9/00 , G06K9/46 , G06K9/44 , G06K9/62 , G06K9/38 , G06T7/00
CPC分类号： G06K9/00127 , G06T7/0012
摘要： 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.

5. 发明公开

EP0731667A1 COMPUTERIZED RADIOGRAPHIC ANALYSIS OF BONE 失效
标题翻译：计算机辅助骨组织的X射线分析
公开(公告)号：EP0731667A1
公开(公告)日：1996-09-18
申请号：EP95903553.0
申请日：1994-11-29
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , DOI, Kunio
IPC分类号： A61B6 , G06F19 , G06T7
CPC分类号： G06T7/0012 , A61B6/4042 , A61B6/482 , A61B6/505 , A61B6/583 , G06T2207/10116 , G06T2207/30008 , G06T2207/30012
摘要： 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.

6. 发明公开

EP0998721A1 METHOD FOR DETECTING INTERVAL CHANGES IN RADIOGRAPHS 失效
标题翻译：用于确定期改变在X线片
公开(公告)号：EP0998721A1
公开(公告)日：2000-05-10
申请号：EP98936980.6
申请日：1998-07-24
申请人： Arch Development Corporation
发明人： DOI, Kunio , ISHIDA, Takayuki , KATSURAGAWA, Shigehiko
IPC分类号： G06K9/60
CPC分类号： G06T7/0016 , G06T3/0081 , G06T5/50 , G06T7/254 , G06T7/337 , G06T2207/10116 , G06T2207/30061
摘要： A method and computerized automated initial image matching algorithm technique for enhancing detection of interval changes between temporally subsequent radiographic images via image subtraction. The method includes the steps of digitizing images (100), normalizing density and contrast in the digital images (102), correcting for lateral inclination in the digital images (104), detecting edges of a same feature in each image (106), converting the images into low resolution matrices (108), blurring the low resolution images (110), segmenting portions of the blurred low resolution matrices based on the detected edges (112), matching the digital images based on a cross-correlation match between the segmented portions, performing non-linear warping to further match Regions of Interest (ROI), and performing image subtraction between the matched digital images (120). The low resolution matrices are greater than 64x64 in size and are produced by averaging. Blurring of the low resolution matrices is performed via a Gaussian filter that removes fine structure in each image such as small vessels, bronchia, etc. The method may be performed by a computer system according to instructions stored on a computer readable medium.

7. 发明公开

EP0760624A1 AUTOMATED DETECTION OF LESIONS IN COMPUTED TOMOGRAPHY 有权
标题翻译：自动检测病变计算出
公开(公告)号：EP0760624A1
公开(公告)日：1997-03-12
申请号：EP95914166.0
申请日：1995-03-30
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , BAE, Kyongtae (Ty) , DOI, Kunio
IPC分类号： A61B6 , G06T1 , G06T7
CPC分类号： G06T7/0012 , G06T2207/10081 , G06T2207/30064 , Y10S378/901
摘要： A method and system for the automated detection of lesions in computed tomographic images, including generating image data from at least one selected portion of an object, for example, from CT images of the thorax. The image data are then analyzed in order to produce the boundary of the thorax. The image data within the thoracic boundary is then further analyzed to produce boundaries of the lung regions using predetermined criteria. Features within the lung regions are then extracted using multi-gray-level thresholding and correlation between resulting multi-level threshold images and between at least adjacent sections. Classification of the features as abnormal lesions or normal anatomic features is then performed using geometric features yielding a likelihood of being an abnormal lesion along with its location in either the 2-D image section or in the 3-D space of the object.

8. 发明公开

EP0731952A1 AUTOMATED METHOD AND SYSTEM FOR IMPROVED COMPUTERIZED DETECTION AND CLASSIFICATION OF MASSES IN MAMMOGRAMS 失效
标题翻译： FOR乳房X线照片改进计算机化的检测和分类大众的自动方法和系统
公开(公告)号：EP0731952A1
公开(公告)日：1996-09-18
申请号：EP95903554.0
申请日：1994-11-29
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , DOI, Kunio , LU, Ping , HUO, Zhimin
IPC分类号： A61B6 , G06K9 , G06T1 , G06T7
CPC分类号： G06K9/00127 , G06T7/0012
摘要： 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.

9. 发明授权

EP0760624B2 AUTOMATED DETECTION OF LESIONS IN COMPUTED TOMOGRAPHY 有权
标题翻译：自动检测病变计算出
公开(公告)号：EP0760624B2
公开(公告)日：2003-07-23
申请号：EP95914166.4
申请日：1995-03-30
申请人： ARCH DEVELOPMENT CORPORATION
发明人： GIGER, Maryellen, L. , BAE, Kyongtae (Ty) , DOI, Kunio
IPC分类号： G06T7/00 , G06F19/00 , A61B6/03
CPC分类号： G06T7/0012 , G06T2207/10081 , G06T2207/30064 , Y10S378/901

10. 发明公开

EP1295244A2 METHOD, SYSTEM AND COMPUTER READABLE MEDIUM FOR ITERATIVE IMAGE WARPING PRIOR TO TEMPORAL SUBTRACTION OF CHEST RADIOGRAPHS IN THE DETECTION OF INTERVAL CHANGES 审中-公开
标题翻译：方法，系统和计算机可读介质的迭代图像成形前乳房RADIO图的时间的减法运算相对于内部变化的诊断
公开(公告)号：EP1295244A2
公开(公告)日：2003-03-26
申请号：EP99917300.8
申请日：1999-04-02
申请人： Arch Development Corporation
发明人： ISHIDA, Takayuki,Hiroshima State University , KATSURAGAWA, Shigehiko , DOI, Kunio
IPC分类号： G06K9/00
CPC分类号： G06T7/0016 , G06T3/0068 , G06T7/254 , G06T7/337 , G06T2207/30061
摘要： 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).
摘要翻译：时间连续的数字图像的计算机分析，的方法，包括（a）第一数字图像的像素和第二数字图像的对应像素之间具有确定性采矿第一位移值; （B）翘曲基于所述第一位移值的第二数字图像，以获得第一变形图像中的哪些像素的空间位置是在相对于第一位移值变化; （C）第一变形的图像的所述第一数字图像的像素与像素之间的确定性采矿第二位移值; 和（d）翘曲基于第二位移值，第一扭曲图像以获得第二变形的图像，其中所述第一变形的图像的像素的空间位置是相对于所述第二位移值变化。图像变形的额外的迭代是可能的，以增强所述第一数字图像和第二数字图像的扭曲版本之间的图像配准，其次是第一数字图像的图像相减和最终变形的图像，以产生从时空哪个诊断的差分图像变化随之而来。时间减影有助于检测胸片间隔变化的放射科医师，尤其涉及克服在时间上连续的图像位置偏移严重误差主要是由于在受试者的倾斜和/或旋转的差异。在生产中的图像变形使用移位值，初始位移值通过使用所关注的模板和搜索区域互相关技术获得。移矢量和在每个肺移矢量的直方图是从初始位移值获得。移矢量的直方图中的组位移值的平滑化的选择中使用的，使用二维拟合和随后使用的拟合值在图像变形移位。

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