Automatic slice selection in medical imaging

    公开(公告)号:US12165308B2

    公开(公告)日:2024-12-10

    申请号:US17047102

    申请日:2019-04-12

    Abstract: A medical imaging system (100, 300, 400, 700) includes a processor and memory with instructions executable by the processor to receive (200) three-dimensional medical image data (122) comprising multiple slices, receive (202) an imaging modality (124) of the three-dimensional medical image data, receive (204) an anatomical view classification (126) of the three-dimensional medical image data, select (206) a chosen abnormality detection module (130) from a set of abnormality detection modules (128) using the imaging modality and the anatomical view classification, wherein at least a portion of the abnormality detection modules is a convolution neural network trained for identifying if the at least a portion of the multiple slices as either normal or abnormal, classify (208) the at least a portion of the multiple slices as normal or abnormal using the abnormality detection module, and choose (210) a set of selected slices (136) from the multiple slices according to a predetermined selection criteria (134) if a predetermined number of the multiple slices are classified as abnormal.

    Invoking chatbot in online communication session

    公开(公告)号:US11616740B2

    公开(公告)日:2023-03-28

    申请号:US17276383

    申请日:2019-09-10

    Abstract: A chatbot may be invoked in an online communication session between two or more human users to share additional content in the communication session. To determine when to invoke the chatbot, e.g., at which point during their conversation, an interaction model may be trained on past conversation data between participants to determine so-termed interaction points in the past conversation data which are predictive of a subsequent sharing of additional content by one of the participants. Having generated the interaction model, the interaction model may be applied to an online communication session to detect such interaction points in a real-time or near real-time conversation between users and to invoke the chatbot to participate in the communication session in response to a detection.

    SYSTEMS AND METHODS FOR EFFICIENTLY ZOOMING AND SCROLLING ALERTS TIMELINE

    公开(公告)号:US20250036271A1

    公开(公告)日:2025-01-30

    申请号:US18776317

    申请日:2024-07-18

    Abstract: An alert monitoring method includes receiving alerts generated by one or more medical systems, each alert being timestamped and associated to the medical system that generated the alert; segmenting a displayed time span into discrete time units whose size depends on the displayed time span; generating a timeline representing the alerts over the displayed time span, the timeline comprising a two-dimensional grid of blocks with each block having a corresponding discrete time unit and a corresponding alert source for the one or more medical systems, and each block being color coded based on a fraction of the corresponding discrete time unit over which the corresponding alert is critical; displaying, on a display device, the timeline representing the alerts over the displayed time span; and in response to receiving a user input adjusting the displayed time span, displaying an updated timeline representing the alerts over the updated displayed time span.

    System and method for generating textual descriptions from medical images

    公开(公告)号:US11056227B2

    公开(公告)日:2021-07-06

    申请号:US15987164

    申请日:2018-05-23

    Abstract: A method for generating a textual description from a medical image, comprising: receiving a medical image having a first modality to a system configured to generate a textual description of the medical image; determining, using an imaging modality classification module, that the first modality is a specific one of a plurality of different modalities; determining, using an anatomy classification module, that the medical image comprises information about a specific portion of an anatomy; identifying, by an orchestrator module based at least on the determined first modality, which of a plurality of different text generation models to utilize to generate a textual description from the medical image; generating, by a text generation module utilizing the identified text generation model, a textual description from the medical image; and reporting, via a user interface of the system, the generated textual description.

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