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公开(公告)号：US11769584B2
公开(公告)日：2023-09-26
申请号：US17481277
申请日：2021-09-21
IPC分类号： G06K9/00 , G16H10/20 , G16H30/20 , G06T7/00 , G06T11/00 , G06F9/455 , A61B5/00 , H04L9/32 , G16H10/60 , G16H30/40 , G06F9/451 , H04L9/40
CPC分类号： G16H30/20 , A61B5/0013 , A61B5/0022 , A61B5/4064 , G06F9/451 , G06F9/45558 , G06T7/0012 , G06T11/00 , G16H10/60 , G16H30/40 , H04L9/32 , H04L63/0428 , G06T2207/20092 , G06T2207/30016
摘要： A cloud computing system is described that communicates with a virtual machine to reattach the face of a patient to brain imaging data before the brain imaging data is transmitted for display on a brain navigation system.
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公开(公告)号：US11704870B2
公开(公告)日：2023-07-18
申请号：US17481261
申请日：2021-09-21
CPC分类号： G06T17/20 , A61B5/0042 , A61B5/055 , G01R33/5608 , G01R33/56341 , G16H30/40 , G16H50/50 , G06T2200/24 , G06T2210/41
摘要： A system and method of generating a graphical representation of a network of a subject human brain. The method comprises receiving, via a user interface, a selection of the network of the subject brain; determining, based on an MRI image of the subject brain and one or more identifiers associated with the selection, one or more parcellations of the subject brain (405); determining, using three-dimensional coordinates associated with each parcellation, corresponding tracts in a diffusion tensor image of the brain (425); and generating a graphical representation of the selected network (430), the graphical representation including at least one of (i) one or more surfaces representing the one or more parcellations, each surface generated using the coordinates, and (ii) the determined tracts.
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公开(公告)号：US11515041B1
公开(公告)日：2022-11-29
申请号：US17465811
申请日：2021-09-02
摘要： Disclosed herein are systems and methods for interactive graphical user interfaces (GUIs) that users (e.g., medical professionals) can use to interact with modelled versions of brains and easily and intuitively analyze deep and/or lateral structures in the brain. A user can, for example, selectively view structures and their connectivity data (e.g., nodes and edges) relative to other structures and connectivity data over a representation of a particular patient's brain. Emphasis can be minimized for certain foreground nodes and edges (e.g., lateral structures) to make it easier for the user to focus on and analyze deeper structures that otherwise can be challenging to visualize and understand. A method can include overlaying deep and non-deep nodes on a representation of a brain, displaying the representation of the brain in a GUI, receiving user input indicating interest in focusing on one or more deep nodes, and taking an action based on the input.
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公开(公告)号：US11382514B1
公开(公告)日：2022-07-12
申请号：US17521687
申请日：2021-11-08
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating explainability data that explains a medical condition in a subject. In one aspect, a method comprises: obtaining data identifying a plurality of brain parcels that are predicted to be relevant to the medical condition; receiving fMRI data for a brain of a subject; processing the fMRI data for the brain of the subject to determine a respective activation score for each of the plurality of brain parcels that are predicted to be relevant to the medical condition; determining, for each of the plurality of brain parcels that are predicted to be relevant to the medical condition, a relative activation score for the brain parcel; and taking an action based on the relative activation scores.
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公开(公告)号：US11315248B2
公开(公告)日：2022-04-26
申请号：US17337365
申请日：2021-06-02
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying one or more invalid images characterizing the brain of a patient. One of the methods includes obtaining a data object comprising one or more images characterizing a brain of a patient; processing the data object to determine one or more particular images that are invalid; and providing, for display to a user on a graphical interface, data characterizing i) each particular image and ii) a respective reason that each particular image is invalid selected from a set of possible reasons that an image may be invalid.
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公开(公告)号：US20220005272A1
公开(公告)日：2022-01-06
申请号：US17481261
申请日：2021-09-21
摘要： A system and method of generating a graphical representation of a network of a subject human brain. The method comprises receiving, via a user interface, a selection of the network of the subject brain; determining, based on an MRI image of the subject brain and one or more identifiers associated with the selection, one or more parcellations of the subject brain (405); determining, using three-dimensional coordinates associated with each parcellation, corresponding tracts in a diffusion tensor image of the brain (425); and generating a graphical representation of the selected network (430), the graphical representation including at least one of (i) one or more surfaces representing the one or more parcellations, each surface generated using the coordinates, and (ii) the determined tracts.
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公开(公告)号：US11152123B1
公开(公告)日：2021-10-19
申请号：US17145240
申请日：2021-01-08
IPC分类号： G16H50/70 , G06N3/08 , G16H40/67 , G16H50/20 , G16H50/30 , G16H20/30 , A61B5/055 , G01R33/48 , G01R33/563 , A61B5/00 , G16H30/20 , G16H30/40
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing brain data using autoencoder neural networks. One of the methods includes obtaining brain data captured by one or more sensors characterizing brain activity of a patient; processing the brain data to generate modified brain data that characterizes a predicted local effect of a future treatment on the brain of the patient; processing the modified brain data using an autoencoder neural network to generate reconstructed brain data; and determining, using the reconstructed brain data, a predicted global effect of the future treatment on the brain of the patient.
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公开(公告)号：US11147454B1
公开(公告)日：2021-10-19
申请号：US17180556
申请日：2021-02-19
摘要： A pre-event connectome of a subject brain is accessed, the pre-event connectome defining i) first functional nodes in the subject brain and ii) first edges that represent connections between the first functional nodes before the subject has undergone an event. A post-event connectome of the subject brain is accessed, the post-event connectome defining i) second functional nodes in the subject brain and ii) second edges that represent connections between the second functional nodes after the subject has undergone the event. A connectome-difference map data is generated that records the difference between the pre-event connectome and the post-event connectome. An action is taken based on the connectome-difference map data.
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公开(公告)号：US11055849B2
公开(公告)日：2021-07-06
申请号：US17066171
申请日：2020-10-08
IPC分类号： G06T7/00 , G06T7/30 , G01R33/563 , G01R33/56
摘要： A method (400) including: determining (702) a registration function [705, Niirf(T1)] for the particular brain in a coordinate space, determining (706) a registered atlas [708, Ard(T1)] from the registration function and an HCP-MMP1 Atlas (102) containing a standard parcellation scheme, performing (310, 619) diffusion tractography to determine a set [621, DTIp(DTI)] of brain tractography images of the particular brain, for a voxel in a particular parcellation in the registered atlas, determining (1105, 1120) voxel level tractography vectors [1123, Vje, Vjn] showing connectivity of the voxel with voxels in other parcellations, classifying (1124) the voxel based on the probability of the voxel being part of the particular parcellation, and repeating (413) the determining of the voxel level tractography vectors and the classifying of the voxels for parcellations of the HCP-MMP1 Atlas to form a personalised brain atlas [1131, PBs Atlas] containing an adjusted parcellation scheme reflecting the particular brain (Bbp).
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公开(公告)号：US11768265B2
公开(公告)日：2023-09-26
申请号：US17746839
申请日：2022-05-17
IPC分类号： G01V3/00 , G01R33/563 , G06N3/08 , G01R33/56 , G06F18/214
CPC分类号： G01R33/56341 , G01R33/5608 , G06F18/214 , G06N3/08
摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for harmonizing diffusion tensor images. One of the methods includes obtaining a diffusion tensor image; determining a set of RISH features for the diffusion tensor image; processing a model input generated from the set of RISH features using a machine learning model to generate a model output identifying an image transformation from a set of image transformations, wherein each image transformation in the set of image transformations corresponds to a respective different first MRI scanner and represents a transformation that, when applied to first diffusion tensor images captured by the first MRI scanner, harmonizes the first diffusion tensor images with second diffusion tensor images captured by a reference MRI scanner; and processing the diffusion tensor image using the identified image transformation to generate a harmonized diffusion tensor image.
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