公开(公告)号：US10718839B2

公开(公告)日：2020-07-21

申请号：US15799025

申请日：2017-10-31

Applicant: GE Precision Healthcare LLC

Inventor： Yongchuan Lai ,  Xiaoli Zhao ,  Weiwei Zhang ,  Stephen Joseph Garnier ,  Lisha Nie ,  Pengfei Lu ,  Hongbin Wang

IPC: G01R33/56 ,  G01R33/36 ,  G01R33/34 ,  G01R33/565 ,  G01R33/3415

Abstract: The present invention provides a method and apparatus for correcting a uniformity of a magnetic resonance image, the method including: acquiring a first uniformity enhancement image by a phased-array uniformity enhancement method; and dividing the first uniformity enhancement image by a receiving sensitivity distribution value of a body coil in a magnetic resonance imaging device, so as to acquire a second uniformity enhancement image. The method further includes: dividing the second uniformity enhancement image by a spatial signal distribution value resulting from a field strength distribution of a transmitting radio-frequency field, so as to acquire a third uniformity enhancement image.

公开(公告)号：US20240118356A1

公开(公告)日：2024-04-11

申请号：US17938465

申请日：2022-10-06

Applicant: GE Precision Healthcare LLC

Inventor： Xiaoli Zhao ,  Kang Wang ,  Hua Li ,  Zhenghui Zhang ,  Florian Wiesinger ,  Ty A. Cashen ,  Rolf Schulte

IPC: G01R33/20 ,  A61B5/055

CPC classification number: G01R33/20 ,  A61B5/055 ,  G01R33/5611

Abstract: A method for generating an image of an object with a magnetic resonance imaging (MM) system is presented. The method includes first performing a calibration scan of the object. The calibration scan is performed with a zero echo time (ZTE) radial sampling scheme to obtain calibration k-spaces for surface coil elements and a body coil of the MRI system. The calibration scan is performed in such a manner that the endpoints of calibration k-space lines in each calibration k-space follow a spiral path. A plurality of calibration parameters are then obtained from the plurality of calibration k-spaces. A second scan of the object is then performed to acquire the MR image data. The image of the object is then generated based on the plurality of calibration parameters and the MR image data.

公开(公告)号：US20210018583A1

公开(公告)日：2021-01-21

申请号：US16514906

申请日：2019-07-17

Applicant: GE Precision Healthcare LLC

Inventor： Dawei Gui ,  Xiaoli Zhao ,  Ling Sun ,  Haonan Wang ,  Wei Sun

IPC: G01R33/565 ,  G06T5/00 ,  G06T7/194 ,  G01R33/56 ,  G01R33/58 ,  G06N3/08

Abstract: Methods and systems are provided for predicting B1+ field maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (B1+ field map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the B1+ field map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict B1+ field maps from MR calibration images.

公开(公告)号：US12078696B2

公开(公告)日：2024-09-03

申请号：US17938465

申请日：2022-10-06

Applicant: GE Precision Healthcare LLC

Inventor： Xiaoli Zhao ,  Kang Wang ,  Hua Li ,  Zhenghui Zhang ,  Florian Wiesinger ,  Ty A. Cashen ,  Rolf Schulte

IPC: G01V3/00 ,  A61B5/055 ,  G01R33/20 ,  G01R33/561

CPC classification number: G01R33/20 ,  A61B5/055 ,  G01R33/5611

Abstract: A method for generating an image of an object with a magnetic resonance imaging (MM) system is presented. The method includes first performing a calibration scan of the object. The calibration scan is performed with a zero echo time (ZTE) radial sampling scheme to obtain calibration k-spaces for surface coil elements and a body coil of the MRI system. The calibration scan is performed in such a manner that the endpoints of calibration k-space lines in each calibration k-space follow a spiral path. A plurality of calibration parameters are then obtained from the plurality of calibration k-spaces. A second scan of the object is then performed to acquire the MR image data. The image of the object is then generated based on the plurality of calibration parameters and the MR image data.

公开(公告)号：US11009578B2

公开(公告)日：2021-05-18

申请号：US16514906

申请日：2019-07-17

Applicant: GE Precision Healthcare LLC

Inventor： Dawei Gui ,  Xiaoli Zhao ,  Ling Sun ,  Haonan Wang ,  Wei Sun

IPC: G06K9/00 ,  A61B6/00 ,  G01R33/565 ,  G06T5/00 ,  G06T7/194 ,  G01R33/56 ,  G06N3/08 ,  G01R33/58

Abstract: Methods and systems are provided for predicting B1+ field maps from magnetic resonance calibration images using deep neural networks. In an exemplary embodiment a method for magnetic resonance imaging comprises, acquiring a magnetic resonance (MR) calibration image of an anatomical region, mapping the MR calibration image to a transmit field map (B1+ field map) with a trained deep neural network, acquiring a diagnostic MR image of the anatomical region, and correcting inhomogeneities of a transmit field in the diagnostic MR image with the B1+ field map. Further, methods and systems are provided for collecting and processing training data, as well as utilizing the training data to train a deep learning network to predict B1+ field maps from MR calibration images.