Patents by Inventor Brandon ROTHROCK
Brandon ROTHROCK has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240062372Abstract: Systems and methods are described herein for processing electronic medical images to predict a biomarker's presence, including receiving one or more digital medical images, the one or more digital medical images being of at least one pathology specimen associated with a patient. A machine learning system may determine a biomarker expression level prediction for the one or more digital medical images. The biomarker expression level prediction may be based on a determined transcriptomic score and protein expression score for the one or more digital medical images. A slide overlay indicating a region of tissue on the one or more digital medical images that is most likely to contribute to the slide level biomarker expression prediction may be generated.Type: ApplicationFiled: August 17, 2023Publication date: February 22, 2024Inventors: Jillian SUE, Marc GOLDFINGER, Brandon ROTHROCK, Matthew LEE
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Publication number: 20230360414Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.Type: ApplicationFiled: July 3, 2023Publication date: November 9, 2023Inventors: Brandon ROTHROCK, Jillian SUE, Matthew HOULISTON, Patricia RACITI, Leo GRADY
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Patent number: 11721115Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.Type: GrantFiled: November 5, 2021Date of Patent: August 8, 2023Assignee: Paige.AI, Inc.Inventors: Brandon Rothrock, Jillian Sue, Matthew Houliston, Patricia Raciti, Leo Grady
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Publication number: 20230245477Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: ApplicationFiled: March 20, 2023Publication date: August 3, 2023Inventors: Brandon ROTHROCK, Christopher KANAN, Julian VIRET, Thomas FUCHS, Leo GRADY
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Patent number: 11663838Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.Type: GrantFiled: October 27, 2021Date of Patent: May 30, 2023Assignee: Paige.AI, Inc.Inventors: Brandon Rothrock, Jillian Sue, Matthew Houliston, Patricia Raciti, Leo Grady
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Patent number: 11640719Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: GrantFiled: July 12, 2022Date of Patent: May 2, 2023Assignee: Paige.AI, Inc.Inventors: Brandon Rothrock, Christopher Kanan, Julian Viret, Thomas Fuchs, Leo Grady
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Publication number: 20220358650Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.Type: ApplicationFiled: July 20, 2022Publication date: November 10, 2022Inventors: Antoine SAINSON, Brandon ROTHROCK, Razik YOUSFI, Patricia RACITI, Matthew HANNA, Christopher KANAN
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Publication number: 20220343508Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: ApplicationFiled: July 12, 2022Publication date: October 27, 2022Inventors: Brandon ROTHROCK, Christopher KANAN, Julian VIRET, Thomas FUCHS, Leo GRADY
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Patent number: 11430117Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.Type: GrantFiled: October 4, 2021Date of Patent: August 30, 2022Assignee: PAIGE.AI, Inc.Inventors: Antoine Sainson, Brandon Rothrock, Razik Yousfi, Patricia Raciti, Matthew Hanna, Christopher Kanan
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Patent number: 11430116Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.Type: GrantFiled: September 9, 2021Date of Patent: August 30, 2022Assignee: PAIGE.AI, Inc.Inventors: Antoine Sainson, Brandon Rothrock, Razik Yousfi, Patricia Raciti, Matthew Hanna, Christopher Kanan
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Patent number: 11423547Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: GrantFiled: September 21, 2021Date of Patent: August 23, 2022Assignee: Paige.AI, Inc.Inventors: Brandon Rothrock, Christopher Kanan, Julian Viret, Thomas Fuchs, Leo Grady
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Publication number: 20220138450Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.Type: ApplicationFiled: November 5, 2021Publication date: May 5, 2022Inventors: Brandon ROTHROCK, Jillian SUE, Matthew HOULISTON, Patricia RACITI, Leo GRADY
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Publication number: 20220139533Abstract: A method of using a machine learning model to output a task-specific prediction may include receiving a digitized cytology image of a cytology sample and applying a machine learning model to isolate cells of the digitized cytology image. The machine learning model may include identifying a plurality of sub-portions of the digitized cytology image, identifying, for each sub-portion of the plurality of sub-portions, either background or cell, and determining cell sub-images of the digitized cytology image. Each cell sub-image may comprise a cell of the digitized cytology image, based on the identifying either background or cell. The method may further comprise determining a plurality of features based on the cell sub-images, each of the cell sub-images being associated with at least one of the plurality of features, determining an aggregated feature based on the plurality of features, and training a machine learning model to predict a target task based on the aggregated feature.Type: ApplicationFiled: October 27, 2021Publication date: May 5, 2022Inventors: Brandon ROTHROCK, Jillian SUE, Matthew HOULISTON, Patricia RACITI, Leo GRADY
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Publication number: 20220108446Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.Type: ApplicationFiled: October 4, 2021Publication date: April 7, 2022Inventors: Antoine SAINSON, Brandon ROTHROCK, Razik YOUSFI, Patricia RACITI, Matthew HANNA, Christopher KANAN
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Publication number: 20220108444Abstract: Systems and methods are disclosed for identifying formerly conjoined pieces of tissue in a specimen, comprising receiving one or more digital images associated with a pathology specimen, identifying a plurality of pieces of tissue by applying an instance segmentation system to the one or more digital images, the instance segmentation system having been generated by processing a plurality of training images, determining, using the instance segmentation system, a prediction of whether any of the plurality of pieces of tissue were formerly conjoined, and outputting at least one instance segmentation to a digital storage device and/or display, the instance segmentation comprising an indication of whether any of the plurality of pieces of tissue were formerly conjoined.Type: ApplicationFiled: September 9, 2021Publication date: April 7, 2022Inventors: Antoine SAINSON, Brandon ROTHROCK, Razik YOUSFI, Patricia RACITI, Matthew HANNA, Christopher KANAN
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Publication number: 20220005201Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: ApplicationFiled: September 21, 2021Publication date: January 6, 2022Inventors: Brandon ROTHROCK, Christopher KANAN, Julian VIRET, Thomas FUCHS, Leo GRADY
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Patent number: 11176676Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: GrantFiled: January 27, 2021Date of Patent: November 16, 2021Assignee: Paige.AI, Inc.Inventors: Brandon Rothrock, Christopher Kanan, Julian Viret, Thomas Fuchs, Leo Grady
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Publication number: 20210233251Abstract: Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.Type: ApplicationFiled: January 27, 2021Publication date: July 29, 2021Inventors: Brandon ROTHROCK, Christopher KANAN, Julian VIRET, Thomas FUCHS, Leo GRADY