-
公开(公告)号：US20230061428A1
公开(公告)日：2023-03-02
申请号：US17877585
申请日：2022-07-29
申请人： PAIGE.AI, Inc.
摘要： A computer-implemented method for processing medical images, the method may include receiving a plurality of medical images of at least one pathology specimen, the pathology specimen being associated with a patient. The method may further include receiving a gross description, the gross description comprising data about the medical images. The method may next include extracting data from the description. Next, the method may include determining, using a machine learning system, at least one associated location on the medical images for one or more pieces of data extracted. The method may then include outputting a visual indication of the gross description data displayed in relation to the medical images.
-
52.发明申请公开(公告)号：US20230030216A1
公开(公告)日：2023-02-02
申请号：US17938255
申请日：2022-10-05
申请人： PAIGE.AI, Inc.
发明人： Belma DOGDAS , Christopher KANAN , Thomas FUCHS , Leo GRADY , Kenan TURNACIOGLU
摘要： Systems and methods are disclosed for receiving a digital image corresponding to a target specimen associated with a pathology category, wherein the digital image is an image of tissue specimen, determining a detection machine learning model, the detection machine learning model being generated by processing a plurality of training images to output a cancer qualification and further a cancer quantification if the cancer qualification is an confirmed cancer qualification, providing the digital image as an input to the detection machine learning model, receiving one of a pathological complete response (pCR) cancer qualification or a confirmed cancer quantification as an output from the detection machine learning model, and outputting the pCR cancer qualification or the confirmed cancer quantification.
-
53.发明申请公开(公告)号：US20230020368A1
公开(公告)日：2023-01-19
申请号：US17933156
申请日：2022-09-19
申请人： PAIGE.AI, Inc.
摘要： A computer-implemented method may include receiving a collection of unstained digital histopathology slide images at a storage device and running a trained machine learning model on one or more slide images of the collection to infer a presence or an absence of a salient feature. The trained machine learning model may have been trained by processing a second collection of unstained or stained digital histopathology slide images and at least one synoptic annotation for one or more unstained or stained digital histopathology slide images of the second collection. The computer-implemented method may further include determining at least one map from output of the trained machine learning model and providing an output from the trained machine learning model to the storage device.
-
公开(公告)号：US20230008197A1
公开(公告)日：2023-01-12
申请号：US17811090
申请日：2022-07-07
申请人： PAIGE.AI, Inc.
摘要： A computer-implemented method may diagnose invasive lobular carcinoma. The method may include receiving one or more digital images into a digital storage device, applying a trained machine learning module to detect a presence or absence of CDH1 biallelic genetic inactivation and/or CDH1 biallelic mutation from the received one or more digital images, and determining whether the patient has invasive lobular carcinoma using the detected presence or absence of the CDH1 biallelic genetic inactivation and/or CDH1 biallelic mutation as ground truth. The one or more digital images may include images of breast tissue of a patient.
-
公开(公告)号：US20220351368A1
公开(公告)日：2022-11-03
申请号：US17591640
申请日：2022-02-03
申请人： PAIGE.AI, Inc.
IPC分类号： G06T7/00
摘要： A computer-implemented method may identify attributes of electronic images and display the attributes. The method may include receiving one or more electronic medical images associated with a pathology specimen, determining a plurality of salient regions within the one or more electronic medical images, determining a predetermined order of the plurality of salient regions, and automatically panning, using a display, across the one or more salient regions according to the predetermined order.
-
公开(公告)号：US20220293249A1
公开(公告)日：2022-09-15
申请号：US17565629
申请日：2021-12-30
申请人： PAIGE.AI, Inc.
摘要： Systems and methods are disclosed for verifying slide and block quality for testing. The method may comprise receiving a collection of one or more digital images at a digital storage device. The collection may be associated with a tissue block and corresponding to an instance. The method may comprise applying a machine learning model to the collection to identify a presence or an absence of an attribute, determining an amount or a percentage of tissue with the attribute from a digital image in the collection that indicates the presence of the attribute, and outputting a quality score corresponding to the determined amount or percentage.
-
57.发明申请公开(公告)号：US20220293242A1
公开(公告)日：2022-09-15
申请号：US17457451
申请日：2021-12-03
申请人： PAIGE.AI, INC.
摘要： A computer-implemented method may include receiving a collection of unstained digital histopathology slide images at a storage device and running a trained machine learning model on one or more slide images of the collection to infer a presence or an absence of a salient feature. The trained machine learning model may have been trained by processing a second collection of unstained or stained digital histopathology slide images and at least one synoptic annotation for one or more unstained or stained digital histopathology slide images of the second collection. The computer-implemented method may further include determining at least one map from output of the trained machine learning model and providing an output from the trained machine learning model to the storage device.
-
58.发明申请公开(公告)号：US20220292670A1
公开(公告)日：2022-09-15
申请号：US17547695
申请日：2021-12-10
申请人： PAIGE.AI, INC.
摘要： A computer-implemented method may include receiving a collection of unstained digital histopathology slide images at a storage device and running a trained machine learning model on one or more slide images of the collection to infer a presence or an absence of a salient feature. The trained machine learning model may have been trained by processing a second collection of unstained or stained digital histopathology slide images and at least one synoptic annotation for one or more unstained or stained digital histopathology slide images of the second collection. The computer-implemented method may further include determining at least one map from output of the trained machine learning model and providing an output from the trained machine learning model to the storage device.
-
公开(公告)号：US20220111230A1
公开(公告)日：2022-04-14
申请号：US17493917
申请日：2021-10-05
申请人： PAIGE.AI, Inc.
摘要： Systems and methods are disclosed for predicting a resistance index associated with a tumor and surrounding tissue, comprising receiving one or more digital images of a pathology specimen, receiving additional information about a patient and/or a disease associated with the pathology specimen, determining at least one target region of the one or more digital images for analysis and removing a non-relevant region of the one or more digital images, applying a machine learning system to the one or more digital images to determine a resistance index for the target region of the one or more digital images, the machine learning system having been trained using a plurality of training images to predict the resistance index for the target region using a plurality of images of pathology specimens, and outputting the resistance index corresponding to the target region.
-
公开(公告)号：US20220108446A1
公开(公告)日：2022-04-07
申请号：US17492745
申请日：2021-10-04
申请人： PAIGE.AI, Inc.
发明人： Antoine SAINSON , Brandon ROTHROCK , Razik YOUSFI , Patricia RACITI , Matthew HANNA , Christopher KANAN
摘要： 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.
-
-
-
-
-
-
-
-
-
搜索结果
89 条记录 (耗时 0.025 秒)
