公开(公告)号：US20220128640A1

公开(公告)日：2022-04-28

申请号：US17083074

申请日：2020-10-28

Applicant: GE Precision Healthcare LLC

Inventor： Sudhanya Chatterjee ,  Dattesh Shanbhag ,  Suresh Joel

IPC: G01R33/56 ,  A61B5/055 ,  G06T7/00 ,  G01R33/48 ,  G01R33/483 ,  G06K9/62

Abstract: Systems and methods for deep learning based magnetic resonance imaging (MRI) examination acceleration are provided. The method of deep learning (DL) based magnetic resonance imaging (MRI) examination acceleration comprises acquiring at least one fully sampled reference k-space data of a subject and acquiring a plurality of partial k-space of the subject. The method further comprises grafting the plurality of partial k-space with the at least one fully sampled reference k-space data to generate a grafted k-space for accelerated examination. The method further comprises training a deep learning (DL) module using the fully sampled reference k-space data and the grafted k-space to remove the grafting artifacts.

公开(公告)号：US11885862B2

公开(公告)日：2024-01-30

申请号：US17083074

申请日：2020-10-28

Applicant: GE Precision Healthcare LLC

Inventor： Sudhanya Chatterjee ,  Dattesh Shanbhag ,  Suresh Joel

IPC: G01R33/56 ,  A61B5/055 ,  G06T7/00 ,  G01R33/48 ,  G01R33/483 ,  G06F18/22

CPC classification number: G01R33/5608 ,  A61B5/055 ,  G01R33/4818 ,  G01R33/4835 ,  G06F18/22 ,  G06T7/0012 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems and methods for deep learning based magnetic resonance imaging (MRI) examination acceleration are provided. The method of deep learning (DL) based magnetic resonance imaging (MRI) examination acceleration comprises acquiring at least one fully sampled reference k-space data of a subject and acquiring a plurality of partial k-space of the subject. The method further comprises grafting the plurality of partial k-space with the at least one fully sampled reference k-space data to generate a grafted k-space for accelerated examination. The method further comprises training a deep learning (DL) module using the fully sampled reference k-space data and the grafted k-space to remove the grafting artifacts.