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公开(公告)号：US20180300902A1
公开(公告)日：2018-10-18
申请号：US16011224
申请日：2018-06-18
Applicant: Straxcorp Pty Ltd
Inventor： Roger ZEBAZE , Yu PENG
IPC: G06T7/90 , H04N1/60 , H04N1/62 , G06T7/11 , G06T7/10 , G06K9/62 , G06K9/46 , G06T11/00 , G06K9/52
Abstract: A method and system for assigning colours to an image or part thereof, the method comprising: selecting a sequence of colours for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof;determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel I, and f is a preselected function (such as to re-arrange the normalized values); and assigning colours to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colours in the sequence.
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公开(公告)号：US20160225166A1
公开(公告)日：2016-08-04
申请号：US15021752
申请日：2014-09-10
Applicant: STRAXCORP PTY LTD
Inventor： Roger ZEBAZE , Yu PENG
CPC classification number: G06T7/90 , G06K9/4652 , G06K9/52 , G06K9/6215 , G06K9/6218 , G06T7/10 , G06T7/11 , G06T11/001 , G06T2200/04 , G06T2207/20092 , G06T2207/20112 , H04N1/60 , H04N1/62
Abstract: A method and system for assigning colours to an image or part thereof, the method comprising: selecting a sequence of colours for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof; determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel /, and ƒ is a preselected function (such as to re-arrange the normalized values); and assigning colours to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colours in the sequence.
Abstract translation: 一种用于向图像或其一部分分配颜色的方法和系统，所述方法包括：选择用于分配给图像或其一部分的颜色序列; 确定图像或其部分内的最小强度IMIN; 确定图像或其部分内的最大强度IMAX; 并根据所述每个像素或体素i确定相对强度值RIV（i）; （I）其中I（i）是像素或体素的强度，ƒ是预选函数（例如重新排列归一化值）; 以及基于所述序列中的每个颜色的相对强度值和顺序，向所述图像或其一部分中的至少一些像素分配颜色。
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公开(公告)号：US20240071052A1
公开(公告)日：2024-02-29
申请号：US17896164
申请日：2022-08-26
Applicant: StraxCorp Pty. Ltd.
IPC: G06V10/774 , G06T11/00 , G06V20/70
CPC classification number: G06V10/774 , G06T11/008 , G06V20/70
Abstract: A method and system for training a machine learning model for reducing or removing a foreign material or artefacts due to a foreign material from an image of a subject, the method comprising: generating one or more first simulated images from one or more real or simulated images of the foreign material (and optionally artefacts due to the foreign material), and from one or more real images of one or more subjects that are free of the foreign material and of artefacts due to the foreign material, such that the generated simulated images include the foreign material and artefacts due to the foreign material; generating one or more predicted images employing at least the first simulated images with a machine learning network that implements a machine learning model; and training or updating the machine learning model with the machine learning network by reducing or minimizing a difference between the one or more predicted images and ground truth data comprising one or more real or simulated images.
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公开(公告)号：US20180268561A1
公开(公告)日：2018-09-20
申请号：US15756485
申请日：2016-09-02
Applicant: STRAXCORP PTY LTD
Inventor： Roger ZEBAZE , Yu PENG
CPC classification number: G06T7/62 , G06T5/002 , G06T7/0012 , G06T7/12 , G06T7/13 , G06T2207/10081 , G06T2207/20192 , G06T2207/30008 , G06T2207/30172
Abstract: A computer-implemented method for identifying a gap between objects in an image, the method comprising: detecting contours of the objects in the image or in a binarized version thereof; locating at least one path or gap between the objects, in the image or in an intersection region being a portion of the image containing at least respective portions of the objects by: determining representative attenuations or densities of respective one or more rows and columns of the image or of the intersection region, identifying first pixels, being pixels in a column that has a representative attenuation or density of 0, and second pixels, being pixels in a row that has a representative attenuation or density of 0, determining whether there exists a path or gap between two or more boundaries by identifying at least one first or second pixel on each of two or more of the boundaries, and detecting one or more paths between the at least two boundaries; and outputting a result indicative of one or more detected paths.
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公开(公告)号：US20210334968A1
公开(公告)日：2021-10-28
申请号：US17370455
申请日：2021-07-08
Applicant: StraxCorp Pty. Ltd.
Inventor： Yu PENG
Abstract: A computer-implemented image analysis method and system. The method comprises: quantifying one or more features segmented and identified from a medical image of a subject; extracting clinically relevant features from non-image data pertaining to the subject; assessing the features segmented from the medical image and the features extracted from the non-image data with a trained machine learning model; and outputting one or more results of the assessing of the features.
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Patent Agency Ranking
公开(公告)号：US20210134016A1
公开(公告)日：2021-05-06
申请号：US17144734
申请日：2021-01-08
Applicant: Straxcorp Pty Ltd
Inventor： Roger ZEBAZE , Yu PENG
IPC: G06T7/90 , H04N1/62 , H04N1/60 , G06T11/00 , G06T7/10 , G06T7/11 , G06K9/46 , G06K9/52 , G06K9/62
Abstract: A computer-implemented method and system for assigning colours to an image or part thereof. The method comprises: segmenting a cluster of pixels or voxels by pixel or voxel value within the image or part thereof; and (a) highlighting features within the image or part thereof, or (b) obscuring or masking details in the image or part thereof, comprising: assigning a colour to each pixel or voxel in the image or part thereof having a pixel or voxel value in the cluster of pixels or voxels.
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公开(公告)号：US20220147757A1
公开(公告)日：2022-05-12
申请号：US17584752
申请日：2022-01-26
Applicant: StraxCorp Pty. Ltd.
Inventor： Yu PENG
Abstract: A system and method for classifying a structure or material in an image of a subject. The system comprises: a segmenter configured to segment an image into one or more segmentations that correspond to respective structures or materials in the image, and to generate from the segmentations one or more segmentation maps of the image (each of the segmentation maps representing the image) including categorizations of pixels or voxels of the segmentation maps assigned from one or more respective predefined sets of categories; a classifier that implements a classification machine learning model configured to generate, based on the segmentations maps, one or more classifications and to assign to the classifications respective scores indicative of a likelihood that the structure or material, or the subject, falls into the respective classifications; and an output for outputting a result indicative of the classifications and scores.
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公开(公告)号：US20230112205A1
公开(公告)日：2023-04-13
申请号：US17959180
申请日：2022-10-03
Applicant: Straxcorp Pty Ltd
Inventor： Roger ZEBAZE , Yu PENG
Abstract: A method of building an abnormality quantifier comprising: generating at least one selected first dataset comprising measurements of a normal population or sample and at least one second selected dataset comprising measurements of an abnormal population or sample; generating an image or map by imagizing the datasets; identifying a normality zone within the image or map using the first dataset; identifying an abnormality zone within the image or map using the second dataset; determining a definition of abnormality based on a comparison of the normality zone and the abnormality zone; receiving or accessing at least one third dataset comprising measurements of a both known normal and abnormal population or sample; testing the performance of the initially defined abnormality against one or more preset performance criteria; and outputting an abnormality quantifier when optimal performance has been reached.
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公开(公告)号：US20220058418A1
公开(公告)日：2022-02-24
申请号：US17518858
申请日：2021-11-04
Applicant: StraxCorp Pty. Ltd.
Inventor： Yu PENG
Abstract: A system and computer-implemented method for analysing or monitoring a subject, the method comprising: identifying one or more objects of interest that have been segmented from a first image comprising any of a baseline scan, a follow-up scan or a reference image of the subject; identifying predefined landmarks of the objects; determining reference morphometries pertaining to the objects by performing morphometrics on the objects by reference to the landmarks; selecting one or more regions of interest (ROIs) from the objects according to the reference morphometries, comprising identifying respective locations of the ROIs relative to the reference morphometries; performing a first analysis of the one or more ROIs; performing at least one corresponding second analysis of the one or more ROIs in respectively at least one second image comprising any other of a baseline scan, a follow-up scan or a reference image; and generating a comparison of one or more results of the first analysis and one or more corresponding results of the second analysis.
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公开(公告)号：US20210217162A1
公开(公告)日：2021-07-15
申请号：US16081701
申请日：2017-02-28
Applicant: Straxcorp Pty Ltd
Inventor： Roger ZEBAZE , Yu PENG
Abstract: A method of building an abnormality quantifier comprising: generating at least one selected first dataset comprising measurements of a normal population or sample and at least one second selected dataset comprising measurements of an abnormal population or sample; generating an image or map by imagizing the datasets; identifying a normality zone within the image or map using the first dataset; identifying an abnormality zone within the image or map using the second dataset; determining a definition of abnormality based on a comparison of the normality zone and the abnormality zone; receiving or accessing at least one third dataset comprising measurements of a both known normal and abnormal population or sample; testing the performance of the initially defined abnormality against one or more preset performance criteria; and outputting an abnormality quantifier when optimal performance has been reached.
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