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1.发明申请公开(公告)号：US20210113167A1
公开(公告)日：2021-04-22
申请号：US16497764
申请日：2018-03-28
Applicant: HOLOGIC, INC.
Inventor： Haili CHUI , Liyang WEI , Jun GE , Xiangwei ZHANG , Nikolaos GKANATSIOS
Abstract: A method for processing breast tissue image data includes processing the image data to generate a set of image slices collectively depicting the patient's breast; for each image slice, applying one or more filters associated with a plurality of multi-level feature modules, each configured to represent and recognize an assigned characteristic or feature of a high-dimensional object; generating at each multi-level feature module a feature map depicting regions of the image slice having the assigned feature; combining the feature maps generated from the plurality of multi-level feature modules into a combined image object map indicating a probability that the high-dimensional object is present at a particular location of the image slice; and creating a 2D synthesized image identifying one or more high-dimensional objects based at least in part on object maps generated for a plurality of image slices.
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2.发明申请公开(公告)号：US20250140389A1
公开(公告)日：2025-05-01
申请号：US18822675
申请日：2024-09-03
Applicant: Hologic, Inc.
Inventor： Ashwini KSHIRSAGAR , Haili CHUI , Nikolaos GKANATSIOS , Adora DSOUZA , Xiangwei ZHANG
IPC: G16H40/20 , G06Q10/0631 , G06Q10/0639 , G06Q10/1093 , G06T7/00 , G16H10/20 , G16H30/20 , G16H30/40 , G16H50/20 , G16H50/30
Abstract: Examples of the present disclosure describe systems and methods for predicting the reading time and/or reading complexity of a breast image. In aspects, a first set of data relating to the reading time of breast images may be collected from one or more data sources, such as image acquisition workstations, image review workstations, and healthcare professional profile data. The first set of data may be used to train a predictive model to predict/estimate an expected reading time and/or an expected reading complexity for various breast images. Subsequently, a second set of data comprising at least one breast image may be provided as input to the trained predictive model. The trained predictive model may output an estimated reading time and/or reading complexity for the breast image. The output of the trained predictive model may be used to prioritize mammographic studies or optimize the utilization of available time for radiologists.
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3.发明公开公开(公告)号：US20240021297A1
公开(公告)日：2024-01-18
申请号：US18319727
申请日：2023-05-18
Applicant: Hologic, Inc.
Inventor： Ashwini KSHIRSAGAR , Haili CHUI , Nikolaos GKANATSIOS , Adora DSOUZA , Xiangwei ZHANG
IPC: G16H40/20 , G16H30/20 , G16H50/30 , G16H50/20 , G16H30/40 , G16H10/20 , G06Q10/0631 , G06Q10/0639 , G06Q10/1093 , G06T7/00
CPC classification number: G16H40/20 , G16H30/20 , G16H50/30 , G16H50/20 , G16H30/40 , G16H10/20 , G06Q10/06311 , G06Q10/06398 , G06Q10/1097 , G06T7/0012 , G06T2200/24 , G06T2207/20081 , G06T2207/30068
Abstract: Examples of the present disclosure describe systems and methods for predicting the reading time and/or reading complexity of a breast image. In aspects, a first set of data relating to the reading time of breast images may be collected from one or more data sources, such as image acquisition workstations, image review workstations, and healthcare professional profile data. The first set of data may be used to train a predictive model to predict/estimate an expected reading time and/or an expected reading complexity for various breast images. Subsequently, a second set of data comprising at least one breast image may be provided as input to the trained predictive model. The trained predictive model may output an estimated reading time and/or reading complexity for the breast image. The output of the trained predictive model may be used to prioritize mammographic studies or optimize the utilization of available time for radiologists.
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4.发明申请公开(公告)号：US20210098120A1
公开(公告)日：2021-04-01
申请号：US17033372
申请日：2020-09-25
Applicant: Hologic, Inc.
Inventor： Ashwini KSHIRSAGAR , Haili CHUI , Nikolaos GKANATSIOS , Adora DSOUZA , Xiangwei ZHANG
IPC: G16H40/20 , G06T7/00 , G16H30/20 , G16H30/40 , G16H50/20 , G16H50/30 , G16H10/20 , G06Q10/06 , G06Q10/10
Abstract: Examples of the present disclosure describe systems and methods for predicting the reading time and/or reading complexity of a breast image. In aspects, a first set of data relating to the reading time of breast images may be collected from one or more data sources, such as image acquisition workstations, image review workstations, and healthcare professional profile data. The first set of data may be used to train a predictive model to predict/estimate an expected reading time and/or an expected reading complexity for various breast images. Subsequently, a second set of data comprising at least one breast image may be provided as input to the trained predictive model. The trained predictive model may output an estimated reading time and/or reading complexity for the breast image. The output of the trained predictive model may be used to prioritize mammographic studies or optimize the utilization of available time for radiologists.
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5.发明申请公开(公告)号：US20250082292A1
公开(公告)日：2025-03-13
申请号：US18776823
申请日：2024-07-18
Applicant: Hologic, Inc.
Inventor： Haili CHUI , Liyang WEI , Jun GE , Nikolaos GKANATSIOS
Abstract: A method for processing breast tissue image data includes obtaining image data of a patient's breast tissue, processing the image data to generate a set of image slices, the image slices collectively depicting the patient's breast tissue; feeding image slices of the set through each of a plurality of object-recognizing modules, each of the object-recognizing modules being configured to recognize a respective type of object that may be present in the image slices; combining objects recognized by the respective object-recognizing modules to generate a synthesized image of the patient's breast tissue; and displaying the synthesized image.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240315654A1
公开(公告)日：2024-09-26
申请号：US18590033
申请日：2024-02-28
Applicant: Hologic, Inc.
Inventor： Haili CHUI , Liyang WEI , Jun GE , Xiangwei ZHANG , Nikolaos GKANATSIOS
CPC classification number: A61B6/502 , A61B6/025 , G06F18/254 , G06T7/0012 , G06T17/10 , G06V10/806 , G06V10/809 , G06V30/2504 , G06T2207/30068
Abstract: A method for processing breast tissue image data includes processing the image data to generate a set of image slices collectively depicting the patient's breast; for each image slice, applying one or more filters associated with a plurality of multi-level feature modules, each configured to represent and recognize an assigned characteristic or feature of a high-dimensional object; generating at each multi-level feature module a feature map depicting regions of the image slice having the assigned feature; combining the feature maps generated from the plurality of multi-level feature modules into a combined image object map indicating a probability that the high-dimensional object is present at a particular location of the image slice; and creating a 2D synthesized image identifying one or more high-dimensional objects based at least in part on object maps generated for a plurality of image slices.
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7.发明申请公开(公告)号：US20230082494A1
公开(公告)日：2023-03-16
申请号：US17847720
申请日：2022-06-23
Applicant: Hologic, Inc.
Inventor： Haili CHUI , Liyang WEI , Jun GE , Nikolaos GKANATSIOS
Abstract: A method for processing breast tissue image data includes obtaining image data of a patient's breast tissue, processing the image data to generate a set of image slices, the image slices collectively depicting the patient's breast tissue; feeding image slices of the set through each of a plurality of object-recognizing modules, each of the object-recognizing modules being configured to recognize a respective type of object that may be present in the image slices; combining objects recognized by the respective object-recognizing modules to generate a synthesized image of the patient's breast tissue; and displaying the synthesized image.
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公开(公告)号：US20230033601A1
公开(公告)日：2023-02-02
申请号：US17847796
申请日：2022-06-23
Applicant: HOLOGIC, INC.
Inventor： Haili CHUI , Zhenxue JING
Abstract: A method and system for creating a dynamic self-learning medical image network system, wherein the method includes receiving, from a first node initial user interaction data pertaining to one or more user interactions with the one or more initially obtained medical images; training a deep learning algorithm based at least in part on the initial user interaction data received from the node; and transmitting an instance of the trained deep learning algorithm to the first node and/or to one or more additional nodes, wherein at each respective node to which the instance of the trained deep learning algorithm is transmitted, the trained deep learning algorithm is applied to respective one or more subsequently obtained medical images in order to obtain a result.
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公开(公告)号：US20240320827A1
公开(公告)日：2024-09-26
申请号：US18671250
申请日：2024-05-22
Applicant: Hologic, Inc.
Inventor： Haili CHUI , Ashwini KSHIRSAGAR , Xiangwei ZHANG
CPC classification number: G06T7/0012 , G06T7/11 , G06T2207/20081 , G06T2207/30068 , G06T2207/30096
Abstract: A method of correlating regions in an image pair including a cranial-caudal image and a medial-lateral-oblique image. Data from a similarity matching model is received by an ensemble model, the data including at least a matched pair of regions and a first confidence level indicator associated with the matched pair of regions. Data from a geo-matching model is received by the ensemble model, the data from the geo-matching model including at least the matched pair of regions and a second confidence level indicator. A joint probability of correlation is determined by the ensemble model based on evaluation of each of the first and second confidence level by the ensemble matching model, wherein the joint probability of correlation provides a probability that the region in each image correlates to the corresponding region in the other image. The joint probability of correlation is provided to an output device.
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公开(公告)号：US20240225447A1
公开(公告)日：2024-07-11
申请号：US18509061
申请日：2023-11-14
Applicant: HOLOGIC, INC.
Inventor： Haili CHUI , Zhenxue JING
IPC: A61B5/00 , G06F18/21 , G06F18/214 , G06F18/40 , G06N3/04 , G06N3/08 , G06V10/774 , G06V10/82
CPC classification number: A61B5/0033 , G06F18/214 , G06F18/217 , G06F18/40 , G06N3/04 , G06N3/08 , G06V10/774 , G06V10/82 , G06V2201/03
Abstract: A method and system for creating a dynamic self-learning medical image network system, wherein the method includes receiving, from a first node initial user interaction data pertaining to one or more user interactions with the one or more initially obtained medical images; training a deep learning algorithm based at least in part on the initial user interaction data received from the node; and transmitting an instance of the trained deep learning algorithm to the first node and/or to one or more additional nodes, wherein at each respective node to which the instance of the trained deep learning algorithm is transmitted, the trained deep learning algorithm is applied to respective one or more subsequently obtained medical images in order to obtain a result.
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