公开(公告)号：US20200337591A1

公开(公告)日：2020-10-29

申请号：US16394774

申请日：2019-04-25

Applicant: General Electric Company

Inventor： Michael Rotman ,  Rafael Shmuel Brada ,  Sangtae Ahn ,  Christopher Judson Hardy ,  Itzik Malkiel ,  Ron Wein

IPC: A61B5/055 ,  G01R33/565 ,  G01R33/48

Abstract: K-space data obtained from a magnetic resonance imaging scan where motion was detected is split into two parts in accordance with the timing of the motion to produce first and second sets of k-space data corresponding to different poses. Sub-images are reconstructed from the k first and second sets of k-space data, which are used as inputs to a deep neural network which transforms them into a motion-corrected image.

公开(公告)号：US11696700B2

公开(公告)日：2023-07-11

申请号：US16394774

申请日：2019-04-25

Applicant: General Electric Company

Inventor： Michael Rotman ,  Rafael Shmuel Brada ,  Sangtae Ahn ,  Christopher Judson Hardy ,  Itzik Malkiel ,  Ron Wein

IPC: A61B5/055 ,  G01R33/565 ,  G01R33/48 ,  G01R33/56 ,  G01R33/567

CPC classification number: A61B5/055 ,  G01R33/4818 ,  G01R33/56509 ,  G01R33/5608 ,  G01R33/5676

Abstract: K-space data obtained from a magnetic resonance imaging scan where motion was detected is split into two parts in accordance with the timing of the motion to produce first and second sets of k-space data corresponding to different poses. Sub-images are reconstructed from the k first and second sets of k-space data, which are used as inputs to a deep neural network which transforms them into a motion-corrected image.

公开(公告)号：US10996306B2

公开(公告)日：2021-05-04

申请号：US16394791

申请日：2019-04-25

Applicant: General Electric Company

Inventor： Isabelle Heukensfeldt Jansen ,  Sangtae Ahn ,  Christopher Judson Hardy ,  Itzik Malkiel ,  Rafael Shmuel Brada ,  Ron Wein ,  Michael Rotman

IPC: G06T7/20 ,  G01R33/565 ,  G01R33/56 ,  G01R33/48 ,  G06T11/00 ,  G06T7/00 ,  G06K9/62 ,  G06N3/08

Abstract: A magnetic resonance imaging (MRI) system includes control and analysis circuitry having programming to acquire magnetic resonance (MR) data using coil elements of the MRI system, analyze the MR data, and reconstruct the MR data into MR sub-images. The system also includes a trained neural network associated with the control and analysis circuitry to transform the MR sub-images into a prediction relating to a presence and extent of motion corruption in the MR sub-images. The programming of the control and analysis circuitry includes instructions to control operations of the MRI system based at least in part on the prediction of the trained neural network.

公开(公告)号：US20200341100A1

公开(公告)日：2020-10-29

申请号：US16394791

申请日：2019-04-25

Applicant: General Electric Company

Inventor： Isabelle Heukensfeldt Jansen ,  Sangtae Ahn ,  Christopher Judson Hardy ,  Itzik Malkiel ,  Rafael Shmuel Brada ,  Ron Wein ,  Michael Rotman

IPC: G01R33/565 ,  G01R33/56 ,  G01R33/48 ,  G06T11/00 ,  G06T7/00 ,  G06T7/20 ,  G06K9/62 ,  G06N3/08

Abstract: A magnetic resonance imaging (MRI) system includes control and analysis circuitry having programming to acquire magnetic resonance (MR) data using coil elements of the MRI system, analyze the MR data, and reconstruct the MR data into MR sub-images. The system also includes a trained neural network associated with the control and analysis circuitry to transform the MR sub-images into a prediction relating to a presence and extent of motion corruption in the MR sub-images. The programming of the control and analysis circuitry includes instructions to control operations of the MRI system based at least in part on the prediction of the trained neural network.