公开(公告)号：US20240138697A1

公开(公告)日：2024-05-02

申请号：US17973855

申请日：2022-10-26

Applicant: GE Precision Healthcare LLC

Inventor： Dattesh Dayanand Shanbhag ,  Chitresh Bhushan ,  Deepa Anand ,  Kavitha Manickam ,  Dawei Gui ,  Radhika Madhavan

IPC: A61B5/055 ,  G01R33/20

CPC classification number: A61B5/055 ,  G01R33/20 ,  G01R33/5608

Abstract: A method for generating an image of a subject with a magnetic resonance imaging (MRI) system is presented. The method includes first performing a localizer scan of the subject to acquire localizer scan data. A machine learning (ML) module is then used to detect the presence of metal regions in the localizer scan data based on magnitude and phase information of the localizer scan data. Based on the detected metal regions in the localizer scan data, the MRI workflow is adjusted for diagnostic scan of the subject. The image of the subject is then generated using the adjusted workflow.

公开(公告)号：US20230004872A1

公开(公告)日：2023-01-05

申请号：US17365650

申请日：2021-07-01

Applicant: GE PRECISION HEALTHCARE LLC

Inventor： Soumya Ghose ,  Radhika Madhavan ,  Chitresh Bhushan ,  Dattesh Dayanand Shanbhag ,  Deepa Anand ,  Desmond Teck Beng Yeo ,  Thomas Kwok-Fah Foo

IPC: G06N20/20 ,  G06K9/62 ,  G06T7/00

Abstract: A computer implemented method is provided. The method includes establishing, via multiple processors, a continuous federated learning framework including a global model at a global site and respective local models derived from the global model at respective local sites. The method also includes retraining or retuning, via the multiple processors, the global model and the respective local models without sharing actual datasets between the global site and the respective local sites but instead sharing synthetic datasets generated from the actual datasets.

公开(公告)号：US20220301163A1

公开(公告)日：2022-09-22

申请号：US17203196

申请日：2021-03-16

Applicant: GE Precision Healthcare LLC

Inventor： Florintina C. ,  Deepa Anand ,  Dattesh Dayanand Shanbhag ,  Chitresh Bhushan ,  Radhika Madhavan

IPC: G06T7/00 ,  G06N20/00 ,  G06T7/11 ,  G06T3/00

Abstract: A medical imaging system includes at least one medical imaging device providing image data of a subject and a processing system programmed to generate a plurality of training images having simulated medical conditions by blending a pathology region from a plurality of template source images to a plurality of target images. The processing system is further programmed to train a deep learning network model using the plurality of training images and input the image data of the subject to the deep learning network model. The processing system is further programmed to generate a medical image of the subject based on the output of the deep learning network model.

公开(公告)号：US20240280654A1

公开(公告)日：2024-08-22

申请号：US18111147

申请日：2023-02-17

Applicant: GE Precision Healthcare LLC

Inventor： Kavitha Manickam ,  Dattesh Dayanand Shanbhag ,  Dawei Gui ,  Chitresh Bhushan

IPC: G01R33/28 ,  G01R33/54

CPC classification number: G01R33/288 ,  G01R33/546

Abstract: A computer-implemented method for performing a scan of a subject utilizing a magnetic resonance imaging (MRI) system includes initiating, via a processor, a prescan of the subject by an MRI scanner of the MRI system without a priori knowledge as to whether the subject has a metal implant. The computer-implemented method also includes executing, via the processor, a metal detection algorithm during a prescan entry point of the prescan to detect whether the metal implant is present in the subject. The computer-implemented method further includes determining, via the processor, to proceed with a calibration scan and the scan utilizing predetermined scan parameters when no metal implant is detected in the subject. The computer-implemented method even further includes switching, via the processor, into a metal implant scan mode when one or more metal implants are detected in the subject.

公开(公告)号：US12048521B2

公开(公告)日：2024-07-30

申请号：US17973855

申请日：2022-10-26

Applicant: GE Precision Healthcare LLC

Inventor： Dattesh Dayanand Shanbhag ,  Chitresh Bhushan ,  Deepa Anand ,  Kavitha Manickam ,  Dawei Gui ,  Radhika Madhavan

IPC: A61B5/055 ,  G01R33/20 ,  G01R33/56

CPC classification number: A61B5/055 ,  G01R33/20 ,  G01R33/5608

Abstract: A method for generating an image of a subject with a magnetic resonance imaging (MRI) system is presented. The method includes first performing a localizer scan of the subject to acquire localizer scan data. A machine learning (ML) module is then used to detect the presence of metal regions in the localizer scan data based on magnitude and phase information of the localizer scan data. Based on the detected metal regions in the localizer scan data, the MRI workflow is adjusted for diagnostic scan of the subject. The image of the subject is then generated using the adjusted workflow.

公开(公告)号：US11776173B2

公开(公告)日：2023-10-03

申请号：US17307517

申请日：2021-05-04

Applicant: GE Precision Healthcare LLC

Inventor： Chitresh Bhushan ,  Dattesh Dayanand Shanbhag ,  Rakesh Mullick

IPC: G06T11/00 ,  G06T7/80 ,  G06T7/11 ,  G06V10/25 ,  A61B5/055 ,  A61B5/00 ,  G06T7/00

CPC classification number: G06T11/008 ,  A61B5/055 ,  A61B5/742 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/80 ,  G06V10/25 ,  G06T2207/10072 ,  G06T2207/20081 ,  G06T2207/30016

Abstract: Techniques are described for generating reformatted views of a three-dimensional (3D) anatomy scan using deep-learning estimated scan prescription masks. According to an embodiment, a system is provided that comprises a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components comprise a mask generation component that employs a pre-trained neural network model to generate masks for different anatomical landmarks depicted in one or more calibration images captured of an anatomical region of a patient. The computer executable components further comprise a reformatting component that reformats 3D image data captured of the anatomical region of the patient using the masks to generate different representations of the 3D image data that correspond to the different anatomical landmarks.

公开(公告)号：US20230293014A1

公开(公告)日：2023-09-21

申请号：US18142726

申请日：2023-05-03

Applicant: GE Precision Healthcare LLC

Inventor： Dattesh Dayanand Shanbhag ,  Rekesh Mullick ,  Arathi Sreekumari ,  Uday Damodar Patil ,  Trevor John Kolupar ,  Chitresh Bhushan ,  Andre de Almeida Maximo ,  Thomas Kwok-Fah Foo ,  Maggie MeiKei Fung

IPC: A61B5/00 ,  A61B5/055

CPC classification number: A61B5/0033 ,  A61B5/055 ,  G06T7/0012

Abstract: The present disclosure relates to use of a workflow for automatic prescription of different radiological imaging scan planes across different anatomies and modalities. The automated prescription of such imaging scan planes helps ensure contiguous visualization of the different landmark structures. Unlike prior approaches, the disclosed technique determines the necessary planes using the localizer images itself and does not explicitly segment or delineate the landmark structures to perform plane prescription.

公开(公告)号：US11506739B2

公开(公告)日：2022-11-22

申请号：US16573955

申请日：2019-09-17

Applicant: GE Precision Healthcare LLC

Inventor： Dawei Gui ,  Dattesh Dayanand Shanbhag ,  Chitresh Bhushan ,  André de Almeida Maximo

IPC: G01V3/00 ,  G01R33/58 ,  G01R33/54 ,  A61B5/055 ,  G06F9/54 ,  G06N3/08 ,  G06N20/00 ,  A61B5/00

Abstract: Methods and systems are provided for determining scan settings for a localizer scan based on a magnetic resonance (MR) calibration image. In one example, a method for magnetic resonance imaging (MRI) includes acquiring an MR calibration image of an imaging subject, mapping, by a trained deep neural network, the MR calibration image to a corresponding anatomical region of interest (ROI) attribute map for an anatomical ROI of the imaging subject, adjusting one or more localizer scan parameters based on the anatomical ROI attribute map, and acquiring one or more localizer images of the anatomical ROI according to the one or more localizer scan parameters.

公开(公告)号：US20250131570A1

公开(公告)日：2025-04-24

申请号：US18491985

申请日：2023-10-23

Applicant: GE Precision Healthcare LLC

Inventor： Muhan Shao ,  Chitresh Bhushan ,  Dattesh Dayanand Shanbhag ,  Kavitha Manickam ,  Dawei Gui

IPC: G06T7/11 ,  A61B5/055 ,  G01R33/48 ,  G01R33/56 ,  G01R33/58 ,  G06T7/73 ,  G06V10/82 ,  G06V20/50 ,  G06V20/70 ,  G16H30/40

Abstract: A method and a system include obtaining calibration scan data or low resolution images of a subject acquired with a magnetic resonance (MR) scanner of an MR imaging system. The method and the system also include inputting the calibration data or the low resolution images into a trained deep learning-based multi-mask segmentation network. The method and the system further include outputting labeled mask images for different anatomical stations, wherein a respective mask of a respective labeled mask image highlights an anatomical landmark of interest in each respective anatomical station of the different anatomical stations. The method and the system even further include determining an extent of a respective anatomical landmark of interest in each respective anatomical station of the different anatomical stations for a respective localizer scan for each respective anatomical station based at least on a respective label mask image for each respective anatomical station.

公开(公告)号：US20250114008A1

公开(公告)日：2025-04-10

申请号：US18483757

申请日：2023-10-10

Applicant: GE Precision Healthcare LLC

Inventor： Dattesh Dayanand Shanbhag ,  Kavitha Manickam ,  Dawei Gui ,  Maggie MeiKei Fung ,  Ting Ye ,  Chitresh Bhushan ,  Muhan Shao

IPC: A61B5/055 ,  A61B5/00 ,  G06T7/00

Abstract: A method for performing a scan of a subject includes receiving a selected protocol for the scan and triggering, upon receiving a start signal, automatic landmarking of the subject on a table of a magnetic resonance imaging (MRI) scanner utilizing a three-dimensional (3D) camera. The method includes obtaining landmark positioning data from the 3D camera and utilizing the landmark positioning data for localization of the region of interest. The method includes, subsequent to the automatic landmarking, triggering a calibration scan of the subject with the MRI scanner and obtaining calibration data from the MRI scanner and utilizing the calibration data for refining the localization of the region of interest. The method includes generating a geometry plan for subsequent scans utilizing both the landmark positioning data and the calibration data and triggering at least one subsequent scan of the subject with the MRI scanner based on the geometry plan.