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

IPC: G06T7/00 ,  G06T7/11

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.

公开(公告)号：US20210035680A1

公开(公告)日：2021-02-04

申请号：US16944995

申请日：2020-07-31

Applicant: Hologic, Inc.

Inventor： Biao CHEN ,  Zhenxue JING ,  Ashwini KSHIRSAGAR ,  Nikolaos GKANATSIOS ,  Haili CHUI

IPC: G16H40/20 ,  G16H50/20 ,  G16H30/40 ,  G16H50/70 ,  G16H70/20 ,  G06Q10/06 ,  G06T7/00 ,  A61B6/02 ,  A61B6/00 ,  A61B8/08

Abstract: Examples of the present disclosure describe systems and methods for automating clinical workflow decisions. In aspects, patient data may be collected from multiple data sources, such as patient records, imaging data, etc. The patient data may be processed using an artificial intelligence (AI) component. The output of the AI component may be used by healthcare professionals to inform healthcare decisions for patients. The output of the AI component and additional information relating to the healthcare decisions and healthcare paths may be provided as input to a decision analysis component. The decision analysis component may process the input and output an automated healthcare recommendation that may be used to further inform the healthcare decisions of the healthcare professionals. In some aspects, the output of the decision analysis component may be used to determine a priority or timeline for performing one or more actions relating to patient healthcare.

公开(公告)号：US20240023916A1

公开(公告)日：2024-01-25

申请号：US18349244

申请日：2023-07-10

Applicant: Hologic, Inc.

Inventor： John W. ROBINSON ,  Kenneth DEFREITAS ,  Adrian HUNSDON ,  Rachel CHANDLER ,  Ashwini KSHIRSAGAR ,  David WOLFF ,  Alan REGO

IPC: A61B6/00 ,  A61B6/04

CPC classification number: A61B6/46 ,  A61B6/0414 ,  A61B6/4435 ,  A61B6/502 ,  A61B6/548

Abstract: A method of imaging a breast of a patient using an imaging system includes applying, with a first component of the imaging system, a compressive force to the breast. A second component of the imaging system is positioned in a start position. The imaging system sends a first guidance signal to the patient. An imaging procedure of the breast is performed with the second component of the imaging system. Subsequent to performing the imaging procedure, a second guidance signal is sent to the patient.

公开(公告)号：US20240242820A1

公开(公告)日：2024-07-18

申请号：US18559456

申请日：2022-05-12

Applicant: Hologic, Inc.

Inventor： Ashwini KSHIRSAGAR ,  Baorui REN ,  Andrew P. SMITH

IPC: G16H30/40 ,  A61B6/00 ,  A61B6/04 ,  A61B6/12 ,  A61B6/50 ,  G16H10/60

CPC classification number: G16H30/40 ,  A61B6/0414 ,  A61B6/12 ,  A61B6/502 ,  A61B6/542 ,  A61B6/545 ,  A61B6/563 ,  G16H10/60

Abstract: Examples of the present disclosure describe systems and methods for using machine learning (ML) to predict optimal exposure technique for acquiring mammographic images. In aspects, training data may be collected from one or more data sources. The training data may comprise sample data of patient attribute data and sample image attribute data, image metadata, image pixel data, and/or exposure technique parameters. The training data may be used to train an ML model to determine the optimal exposure technique parameters for acquiring mammographic images of a patient. After the ML model has been trained, patient data that is collected from a patient during a patient visit may be provided as input to the ML model. The ML model may output optimal exposure technique parameters for the patient in real-time. The real-time output of the ML model may be used to generate one or more mammographic images of the patient.

公开(公告)号：US20220087629A1

公开(公告)日：2022-03-24

申请号：US17407452

申请日：2021-08-20

Applicant: Hologic, Inc.

Inventor： John W. ROBINSON ,  Kenneth DEFREITAS ,  Adrian HUNSDON ,  Rachel CHANDLER ,  Ashwini KSHIRSAGAR ,  David WOLFF ,  Alan REGO

IPC: A61B6/00 ,  A61B6/04

Abstract: A method of imaging a breast of a patient using an imaging system includes applying, with a first component of the imaging system, a compressive force to the breast. A second component of the imaging system is positioned in a start position. The imaging system sends a first guidance signal to the patient. An imaging procedure of the breast is performed with the second component of the imaging system. Subsequent to performing the imaging procedure, a second guidance signal is sent to the patient.

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.

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.

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.