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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
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.
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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
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.
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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
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.
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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
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.
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