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公开(公告)号：DE69517524T3
公开(公告)日：2004-05-13
申请号：DE69517524
申请日：1995-03-30
Applicant: ARCH DEV CORP
Inventor： GIGER L , BAE KYONGTAE TY , DOI KUNIO
Abstract: 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.
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公开(公告)号：AT239273T
公开(公告)日：2003-05-15
申请号：AT95903554
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 , G06T5/00 , G06K9/46 , G06K9/44 , G06K9/62 , G06K9/38
Abstract: A method and system for the automated detection and classification of masses in mammograms. These method and system include the performance of iterative, multi-level gray level thresholding, followed by a lesion extraction and feature extraction techniques for classifying true masses from false-positive masses and malignant masses from benign masses. The method and system provide improvements in the detection of masses include multi-gray-level thresholding 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 of malignancy.
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公开(公告)号：AU4147502A
公开(公告)日：2002-06-11
申请号：AU4147502
申请日：2001-11-21
Applicant: ARCH DEV CORP
Inventor： LI QIANG , KATSURAGAWA SHIGEHIKO , DOI KUNIO
Abstract: A method to determine whether a candidate abnormality in a medical digital image is an actual abnormality, a system which implements the method, and a computer readable medium which stores program steps to implement the method, wherein the method includes obtaining a medical digital image including a candidate abnormality; obtaining plural first templates and plural second templates respectively corresponding to predetermined abnormalities and predetermined non-abnormalities; comparing the candidate abnormality with the obtained first and second templates to derive cross-correlation values between the candidate abnormality and each of the obtained first and second templates; determining the largest cross-correlation value derived in the comparing step and whether the largest cross-correlation value is produced by comparing the candidate abnormality with the first templates or with the second templates; and determining the candidate abnormality to be an actual abnormality when the largest cross-correlation value is produced by comparing the candidate abnormality with the first templates and determining the candidate abnormality to be a non-abnormality when the largest cross-correlation value is produced by comparing the candidate abnormality with the second templates. An actual abnormality is similarly classified as malignant or benign based on further cross-correlation values obtained by comparisons with additional templates corresponding to malignant and benign abnormalities.
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公开(公告)号：DE69517524T2
公开(公告)日：2001-02-08
申请号：DE69517524
申请日：1995-03-30
Applicant: ARCH DEV CORP
Inventor： GIGER L , BAE KYONGTAE TY , DOI KUNIO
Abstract: 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.
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公开(公告)号：AU1606400A
公开(公告)日：2000-06-05
申请号：AU1606400
申请日：1999-11-12
Applicant: ARCH DEV CORP
Inventor： DOI KUNIO , NAKAMURA KATSUMI
Abstract: A method, computer program product, and system (100) for computerized analysis of the likelihood of malignancy in a pulmonary nodule using artificial neural networks (ANNs) (S4). The method, on which the computer program product and the system is based on, includes obtaining a digital outline of a nodule; generating objective measures corresponding to physical features of the outline of the nodule; applying the generated objective measures to an ANN; and determining a likelihood of malignancy of the nodule based on an output of the ANN. Techniques include novel developments and implementations of artificial neural networks and feature extraction for digital images. Output from the inventive method yields an estimate of the likelihood of malignancy (S7) for a pulmonary nodule.
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Patent Agency Ranking
公开(公告)号：AU2868599A
公开(公告)日：1999-09-06
申请号：AU2868599
申请日：1999-02-23
Applicant: ARCH DEV CORP
Inventor： XU XIN-WEI , DOI KUNIO
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 chest radiographic image represented by digital data, including preprocessing the image to identify candidate nodules in the image; establishing a region of interest (ROI) including a candidate nodule identified in the preprocessing step; performing image enhancement of the candidate nodule within the ROI; obtaining a histogram of accumulated edge gradients as a function of radial angles withing the ROI after performing the image enhancement; and determining whether the candidate nodule is a false positive based on the obtained histogram. A 64x64-pixel region of interest (ROI) centered at the candidate location is used. The contrast of the ROI is improved by a two-dimensional background subtraction. A nodule shape matched filter is used for enhancement of the nodular pattern located in the central area of the ROI. Analysis of the histogram resulted in identification of seven features, including (1) a maximum histogram value, (2) a minimum histogram value, (3) a partial average value of the histogram, (4) a standard deviation of the histogram values near the radial axis, (5) a partial standard deviation of histogram values, (6) a width of the histogram including both sides from zero degrees of the radial angle, at a predetermined histogram value, and (7) a ratio of a maximum histogram value near the radial axis to a maximum histogram value in two predetermined outside ranges of the radial axis, useful for the identification and elimination of false positives.
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公开(公告)号：AU1597899A
公开(公告)日：1999-06-16
申请号：AU1597899
申请日：1998-11-25
Applicant: ARCH DEV CORP
Inventor： NISHIKAWA ROBERT M , DOI KUNIO
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公开(公告)号：AU703194B2
公开(公告)日：1999-03-18
申请号：AU1256995
申请日：1994-11-29
Applicant: ARCH DEV CORP
Inventor： GIGER MARYELLEN L , DOI KUNIO
Abstract: A computerized method and system for the radiographic analysis of bone structure and risk of future fracture with or without the measurement of bone mass. Techniques include texture analysis for use in quantitating the bone structure and risk of future fracture. The 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 the bony region of interest. The system also includes using dual energy imaging in order 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 artificial neural networks in order to yield a likelihood of risk of future fracture. In addition, a method and system is presented in which dual-energy imaging techniques are used to yield measures of both bone mass and bone structure with one low-dose radiographic examination; thus, making the system desirable for screening (for osteoporosis and risk of future fracture).
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公开(公告)号：AU8579898A
公开(公告)日：1999-02-16
申请号：AU8579898
申请日：1998-07-24
Applicant: ARCH DEV CORP
Inventor： DOI KUNIO , ISHIDA TAKAYUKI , KATSURAGAWA SHIGEHIKO
Abstract: A method and computerized automated initial image matching technique for enhancing detection of interval changes between temporally subsequent radiographic images via image subtraction. The method includes the steps of digitizing images, normalizing density and contrast in the digital images, correcting for lateral inclination in the digital images, detecting edges of a same feature in each image, converting the images into low resolution matrices, blurring the low resolution images, segmenting portions of the blurred low resolution matrices based on the detected edges, 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. 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 structures 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.
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公开(公告)号：AU698576B2
公开(公告)日：1998-11-05
申请号：AU2127095
申请日：1995-03-30
Applicant: ARCH DEV CORP
Inventor： GIGER MARYELLEN L , BAE KYONGTAE TY , DOI KUNIO
Abstract: 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.
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