CONVERSION AND TRANSFER OF REAL-TIME VOLUMETRIC IMAGE DATA FOR A MEDICAL DEVICE

    公开(公告)号:US20230317252A1

    公开(公告)日:2023-10-05

    申请号:US18041126

    申请日:2021-08-06

    CPC classification number: G16H30/40 G06T15/00 G06V10/44 G06V10/56 G16H30/20

    Abstract: A system may perform operations including receiving data comprising a plurality of image frames sampled from a volume data set of an imaged anatomical region displayable on a monitor. The plurality of image frames may correspond to a plurality of volume data reconstruction images displayed on the monitor in a series of image slices of a scrollable image stack. The operations also include analyzing the plurality of image frames to detect image features that are characteristic of a static view region in each image frame and evaluating the detected image features to determine a relative location of the detected one or more image features with respect to a scrolling view region for each image frame. The operations also include determining an ordered set of the image frames sorted according to a sequence based on relative locations and producing processed video data comprising the ordered set of the image frames.

    SYSTEMS AND METHODS FOR DELIVERING TARGETED THERAPY

    公开(公告)号:US20230071306A1

    公开(公告)日:2023-03-09

    申请号:US17800279

    申请日:2021-02-18

    Abstract: A computer-assisted medical device is configured and used to endoluminally navigate to a location in the gastrointestinal system and there treat certain body lumen wall areas while avoiding other body lumen wall areas. Embodiments ablate the inner mucosal layer and sub-mucosal nerve plexus of the stomach, duodenum and jejunum to effect treatment of insulin resistance and metabolic disorders, such as Type II diabetes (T2D), polycystic ovarian syndrome (PCOS), non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver disease (NAFLD), congestive heart failure (CHF) and obstructive sleep apnea (OSA). Various sensors are used to assist a clinical operator to navigate from the mouth through the pyloric sphincter and into and through the duodenum and/or jejunum. Various sensors are used to map and identify portions of the duodenum and/or jejunum. Various lumen wall ablation devices and methods are described. Various post-treatment assessments are described.

    SYSTEMS AND METHODS FOR INTELLIGENTLY SEEDING REGISTRATION

    公开(公告)号:US20220378517A1

    公开(公告)日:2022-12-01

    申请号:US17839340

    申请日:2022-06-13

    Abstract: A method of registering sets of anatomical data for use during a medical procedure is provided herein. The method may include accessing a first set of model points of a patient anatomy of interest and intra-operatively acquiring a second set of model points by visualizing a portion of the anatomical surface in the patient with a vision probe. The method may further include extracting system information, including kinematic information from a robotic arm of a medical system and/or setup information, and generating an initial seed transformation based on the extracted system information. Thereafter, the method may include applying the initial seed transformation to the first set of model points and generating a first registration between the first set of model points and the second set of model points to permit model and actual information to be viewed and used together by an operator.

    Systems and methods for intraoperative segmentation

    公开(公告)号:US11445934B2

    公开(公告)日:2022-09-20

    申请号:US15329676

    申请日:2015-07-17

    Abstract: A system comprises a medical instrument, including a sensing tool, and a processing unit configured to apply a segmentation function using a first seed to a three-dimensional image of a patient anatomy to create a model; receive position data from the instrument while navigating the patient anatomy; register a position of the instrument with the model; receive data related to the patient anatomy from the sensing tool; and update the model in response to detecting a difference between the model and the patient anatomy. Updating the model includes reapplying the segmentation function using a second seed corresponding to a passageway of the patient anatomy that is not present within the model. Detecting the difference between the model and the patient anatomy includes analyzing temporal information obtained from shape data generated by the sensing tool while the instrument traverses portions of the patient anatomy not represented by the model.

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