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    System and method for analyzing breast support environment
    32.
    发明授权
    System and method for analyzing breast support environment 有权

    公开(公告)号：US12251257B2

    公开(公告)日：2025-03-18

    申请号：US17968932

    申请日：2022-10-19

    Applicant: GE Precision Healthcare LLC

    Inventor： Jerome Sutty ,  Laurence Vancamberg ,  Vincent Croulard

    IPC: A61B6/00 ,  A61B6/02 ,  A61B6/04 ,  A61B6/50 ,  A61B10/02

    Abstract: According to one aspect of an exemplary embodiment of the disclosure, an imaging device or system, e.g., a mammography imaging system or device, includes a distance and location sensing system on the imaging system/e to provide accurate distance and position information from one or more sensing device(s) constituting the system that measure the elapsed time between the emission of the wave or radiation from the sensing device and the detection of the reflected wave or radiation. Examples of the types of sensing devices include ultrasound sensing devices, MEMS radar devices and time-of-flight (ToF) sensing devices. The distance information can be employed to determine the relative positions to produce a distance map illustrating the position and shape of any objects sensed within the zone by the sensing device(s), to determine the rate of change of the positions, i.e., the speed, of the objects relative to one another for use in controlling movement of various components of the imaging system, and to determine the shape of the object and changes in the shape of the object.

    Speed Variable TDS Operation in X-Ray Imaging Systems
    33.
    发明申请
    Speed Variable TDS Operation in X-Ray Imaging Systems 有权

    公开(公告)号：US20250082288A1

    公开(公告)日：2025-03-13

    申请号：US18243343

    申请日：2023-09-07

    Applicant: GE Precision Healthcare LLC

    Inventor： Adam Manders ,  Michael R. Buchholz ,  James Wear

    IPC: A61B6/00

    Abstract: TDS (Time-Delayed Summation) acquisition systems and methods may be used within various imaging device and systems, such as a densitometry system with highly pixelated 2-D detectors and compact x-ray fan beam that scans patients in a rastering pattern across the patient axis. An improved system and method is described for extending the usability of TDS data on each transverse sweep of the scan, by acquiring data when the scan speed is variable. In this method, the TDS shift strobe signal is no longer a constant periodic function. Instead the time between strobes is dependent on the scan velocity and the strobe sequence is generated to provide constant sampling distance between strobes. Thus, the TDS shift sequence insures a constant image pixel size, enabling undistorted images despite the variable speed occurring during the signal summation.

    Dynamic multimodal segmentation selection and fusion
    37.
    发明授权
    Dynamic multimodal segmentation selection and fusion 有权

    公开(公告)号：US12249067B2

    公开(公告)日：2025-03-11

    申请号：US17664702

    申请日：2022-05-24

    Applicant: GE Precision Healthcare LLC

    Inventor： Tao Tan ,  Hongxiang Yi ,  Rakesh Mullick ,  Lehel Mihály Ferenczi ,  Gopal Biligeri Avinash ,  Borbála Deák-Karancsi ,  Balázs Péter Cziria ,  Laszlo Rusko

    IPC: G06T7/00 ,  A61B8/08 ,  G06T7/149 ,  G06T7/174

    Abstract: Techniques are described that facilitate dynamic multimodal segmentation selection and fusion in medical imaging. In one example embodiment, a computer processing system receives a segmentation dataset comprising a combination of different image segmentations of an anatomical object of interest respectively segmented via different segmentation models from different medical images captured of the (same) anatomical object, wherein the different medical images and the different image segmentations vary with respect to at least one of, capture modality, acquisition protocol, or acquisition parameters. The system employs a dynamic ranking protocol as opposed to a static ranking protocol to determine ranking scores for the different image segmentations that control relative contributions of the different image segmentations in association with combining the different image segmentations into a fused segmentation for the anatomical object. The system further combines the different image segmentations based on the ranking scores to generate the fused image segmentation.

    HIGHER BANDWIDTH MICROMACHINED TRANSDUCERS MIXED WITH BIASING SCHEME
    38.
    发明申请
    HIGHER BANDWIDTH MICROMACHINED TRANSDUCERS MIXED WITH BIASING SCHEME 有权

    公开(公告)号：US20250073750A1

    公开(公告)日：2025-03-06

    申请号：US18460440

    申请日：2023-09-01

    Applicant: GE Precision Healthcare LLC

    Inventor： Rupak Bardhan Roy ,  Omid Farhanieh ,  Alessandro Stuart Savoia

    IPC: B06B1/02 ,  A61B8/00

    Abstract: Various methods and systems are provided for increasing a fractional bandwidth of an ultrasound device, for use in both low and high frequency applications. In one example, where a transducer array includes one or more transducer elements comprising a plurality of capacitive micromachined ultrasound transducers (cMUT), the fractional bandwidth may be advantageously increased by applying different bias voltages to different groupings of cMUTs within each transducer element. A ratio between the different bias voltages may be optimized to maximize the fractional bandwidth. In another example, the different bias voltages may be configured to operate a first grouping of cMUTs in a transmit mode, and a second grouping of cMUTs in a receive mode.

    SYSTEM AND METHODS FOR AUTOMATIC IMAGE ALIGNMENT OF THREE-DIMENSIONAL IMAGE VOLUMES
    40.
    发明申请
    SYSTEM AND METHODS FOR AUTOMATIC IMAGE ALIGNMENT OF THREE-DIMENSIONAL IMAGE VOLUMES 有权

    公开(公告)号：US20250069218A1

    公开(公告)日：2025-02-27

    申请号：US18453954

    申请日：2023-08-22

    Applicant: GE Precision Healthcare LLC

    Inventor： Deepa Anand ,  Bipul Das ,  Vanika Singhal ,  Rakesh Mullick ,  Sandeep Dutta ,  Amy L Deubig ,  Maud Bonnard ,  Christine Smith

    IPC: G06T7/00 ,  G06T7/60 ,  G06T15/00 ,  G06V10/24 ,  G06V10/44

    Abstract: The current disclosure provides systems and methods for automatic image alignment of three-dimensional (3D) medical image volumes. The method includes pre-processing the 3D medical image volume by selecting a sub-volume of interest, detecting anatomical landmarks in the sub-volume using a deep neural network, estimating transformation parameters based on the anatomical landmarks to adjust rotation angles and translation of the sub-volume, adjusting the rotation angles and translation to produce a first aligned sub-volume, determining confidence in the transformation parameters based on the first aligned sub-volume, and iteratively refining the transformation parameters if the confidence is below a predetermined threshold. The disclosed approach for automated image alignment reduces the need for manual alignment and, increases a probability of the 3D image volume converging to a desired orientation compared to conventional approaches.

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