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公开(公告)号：US11321839B2
公开(公告)日：2022-05-03
申请号：US17028747
申请日：2020-09-22
Applicant: Applied Materials, Inc.
Inventor： Sumit Kumar Jha , Aditya Sista , Ganesh Kumar Mohanur Raghunathan , Ubhay Kumar , Kedar Sapre
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.
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公开(公告)号：US11688188B2
公开(公告)日：2023-06-27
申请号：US17236739
申请日：2021-04-21
Applicant: Applied Materials, Inc.
Inventor： Parijat Prakash Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Sumit Kumar Jha , Aditya Sista , Narasimha Murthy Chandan
CPC classification number: G06V20/698 , G06N20/00 , G06T7/0012 , G06N3/02 , G06T7/11 , G06T2207/20081 , G06T2207/30024
Abstract: Certain aspects of the present disclosure provide techniques for automatically detecting and classifying tumor regions in a tissue slide. The method generally includes obtaining a digitized tissue slide from a tissue slide database and determining, based on output from a tissue classification module, a type of tissue of shown in the digitized tissue slide. The method further includes determining, based on output from a tumor classification model for the type of tissue, a region of interest (ROI) of the digitized tissue slide and generating a classified slide showing the ROI of the digitized tissue slide and an estimated diameter of the ROI. The method further includes displaying on an image display unit, the classified slide and user interface (UI) elements enabling a pathologist to enter input related to the classified slide.
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公开(公告)号：US20220164952A1
公开(公告)日：2022-05-26
申请号：US17571427
申请日：2022-01-07
Applicant: Applied Materials, Inc.
Inventor： Parijat P. Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Aditya Sista , Sumit Kumar Jha , Narasimha Murthy Chandan
Abstract: An imaging system includes a microscope to generate magnified images of regions of interest of a tissue sample, a camera to capture and store the magnified images, and a controller. The controller is configured to, for each magnification level in a sequence of increasing magnification levels, image one or more regions of interest of the tissue sample at the current magnification level. For each region of interest, data is generated defining one or more refined regions of interest based on the magnified image of the region of interest of the tissue sample at the current magnification level. Each refined region of interest corresponds to a proper subset of the tissue sample, and the refined regions of interest of the tissue sample provide the regions of interest to be imaged at a next magnification level from the sequence of increasing magnification levels.
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公开(公告)号：US20210090251A1
公开(公告)日：2021-03-25
申请号：US17028747
申请日：2020-09-22
Applicant: Applied Materials, Inc.
Inventor： Sumit Kumar Jha , Aditya Sista , Ganesh Kumar Mohanur Raghunathan , Ubhay Kumar , Kedar Sapre
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.
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公开(公告)号：US12211296B2
公开(公告)日：2025-01-28
申请号：US18208655
申请日：2023-06-12
Applicant: Applied Materials, Inc.
Inventor： Parijat Prakash Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Sumit Kumar Jha , Aditya Sista , Narasimha Murthy Chandan
Abstract: Certain aspects of the present disclosure provide techniques for automatically detecting and classifying tumor regions in a tissue slide. The method generally includes obtaining a digitized tissue slide from a tissue slide database and determining, based on output from a tissue classification module, a type of tissue of shown in the digitized tissue slide. The method further includes determining, based on output from a tumor classification model for the type of tissue, a region of interest (ROI) of the digitized tissue slide and generating a classified slide showing the ROI of the digitized tissue slide and an estimated diameter of the ROI. The method further includes displaying on an image display unit, the classified slide and user interface (UI) elements enabling a pathologist to enter input related to the classified slide.
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Patent Agency Ranking
公开(公告)号：US11694331B2
公开(公告)日：2023-07-04
申请号：US17571427
申请日：2022-01-07
Applicant: Applied Materials, Inc.
Inventor： Parijat P. Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Aditya Sista , Sumit Kumar Jha , Narasimha Murthy Chandan
CPC classification number: G06T7/0012 , G06T7/11 , G06T7/143 , G06T2207/30024
Abstract: An imaging system includes a microscope to generate magnified images of regions of interest of a tissue sample, a camera to capture and store the magnified images, and a controller. The controller is configured to, for each magnification level in a sequence of increasing magnification levels, image one or more regions of interest of the tissue sample at the current magnification level. For each region of interest, data is generated defining one or more refined regions of interest based on the magnified image of the region of interest of the tissue sample at the current magnification level. Each refined region of interest corresponds to a proper subset of the tissue sample, and the refined regions of interest of the tissue sample provide the regions of interest to be imaged at a next magnification level from the sequence of increasing magnification levels.
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公开(公告)号：US11663722B2
公开(公告)日：2023-05-30
申请号：US17729377
申请日：2022-04-26
Applicant: Applied Materials, Inc.
Inventor： Sumit Kumar Jha , Aditya Sista , Ganesh Kumar Mohanur Raghunathan , Ubhay Kumar , Kedar Sapre
CPC classification number: G06T7/0012 , G06F18/22 , G06F18/24323 , G06T7/11 , G06V10/25 , G06T2207/10056 , G06T2207/20084 , G06T2207/30024
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.
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公开(公告)号：US20220261992A1
公开(公告)日：2022-08-18
申请号：US17729377
申请日：2022-04-26
Applicant: Applied Materials, Inc.
Inventor： Sumit Kumar Jha , Aditya Sista , Ganesh Kumar Mohanur Raghunathan , Ubhay Kumar , Kedar Sapre
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to segment magnified images of tissue samples. The method includes obtaining a magnified image of a tissue sample; processing an input comprising: the image, features derived from the image, or both, in accordance with current values of model parameters of a machine learning model to generate an automatic segmentation of the image into a plurality of tissue classes; providing, to a user through a user interface, an indication of: (i) the image, and (ii) the automatic segmentation of the image; determining an edited segmentation of the image, comprising applying modifications specified by the user to the automatic segmentation of the image; and determining updated values of the model parameters of the machine learning model based the edited segmentation of the image.
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公开(公告)号：US11232561B2
公开(公告)日：2022-01-25
申请号：US16746569
申请日：2020-01-17
Applicant: Applied Materials, Inc.
Inventor： Parijat P. Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Aditya Sista , Sumit Kumar Jha , Narasimha Murthy Chandan
Abstract: An imaging system includes a microscope to generate magnified images of regions of interest of a tissue sample, a camera to capture and store the magnified images, and a controller. The controller is configured to, for each magnification level in a sequence of increasing magnification levels, image one or more regions of interest of the tissue sample at the current magnification level. For each region of interest, data is generated defining one or more refined regions of interest based on the magnified image of the region of interest of the tissue sample at the current magnification level. Each refined region of interest corresponds to a proper subset of the tissue sample, and the refined regions of interest of the tissue sample provide the regions of interest to be imaged at a next magnification level from the sequence of increasing magnification levels.
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公开(公告)号：US11017207B2
公开(公告)日：2021-05-25
申请号：US16553562
申请日：2019-08-28
Applicant: Applied Materials, Inc.
Inventor： Parijat Prakash Prabhudesai , Ganesh Kumar Mohanur Raghunathan , Sumit Kumar Jha , Aditya Sista , Narasimha Murthy Chandan
Abstract: Certain aspects of the present disclosure provide techniques for automatically detecting and classifying tumor regions in a tissue slide. The method generally includes obtaining a digitized tissue slide from a tissue slide database and determining, based on output from a tissue classification module, a type of tissue of shown in the digitized tissue slide. The method further includes determining, based on output from a tumor classification model for the type of tissue, a region of interest (ROI) of the digitized tissue slide and generating a classified slide showing the ROI of the digitized tissue slide and an estimated diameter of the ROI. The method further includes displaying on an image display unit, the classified slide and user interface (UI) elements enabling a pathologist to enter input related to the classified slide.
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