公开(公告)号：US20250138119A1

公开(公告)日：2025-05-01

申请号：US18499149

申请日：2023-10-31

Applicant: GE Precision Healthcare LLC

Inventor： Ali Ersoz

IPC: G01R33/48 ,  G01R33/565

Abstract: A method for imaging a subject using an magnetic resonance imaging (MR) system is presented. The method includes sampling a k-space in a rotating fashion using a plurality of radially directed blades around a center of the k-space. A first subset of blades is acquired with a positive excitation pulse and a first plurality of refocusing pulses. Further, a second subset of blades is acquired with a negative excitation pulse and a second plurality of refocusing pulses. The polarity of the second subset of blades is inverted to generate a third subset of blades. The first subset of blades and the third subset of blades are then combined to generate a final k-space. Finally, a medical image of the subject is generated based on a reconstruction of the final k-space.

公开(公告)号：US10884086B1

公开(公告)日：2021-01-05

申请号：US16525161

申请日：2019-07-29

Applicant: GE Precision Healthcare LLC

Inventor： Ali Ersoz ,  Ajeetkumar Gaddipati ,  Dawei Gui ,  Valentina Taviani ,  Zachary W Slavens

IPC: G01R33/48 ,  G01R33/561

Abstract: Systems and methods for accelerated multi-contrast PROPELLER are disclosed herein. K-space is sampled in a rotating fashion using a plurality of radially directed blades around a center of k-space. A first subset of blades is acquired for a first contrast and a second subset of blades is acquired for a second contrasts. The first subset of blades is combined with high frequency components of the second subset of blades to produce an image of the first contrast. And the second subset of blades are combined with high frequency components of the first subset of blades to produce an image of the second contrast.

公开(公告)号：US11783451B2

公开(公告)日：2023-10-10

申请号：US16806689

申请日：2020-03-02

Applicant: GE Precision Healthcare LLC

Inventor： Daniel Litwiller ,  Xinzeng Wang ,  Ali Ersoz ,  Robert Marc Lebel ,  Ersin Bayram ,  Graeme Colin McKinnon

IPC: G06T5/00 ,  G06T7/00 ,  A61B6/00

CPC classification number: G06T5/002 ,  A61B6/5258 ,  G06T7/0012 ,  G06T2207/10024 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20182

Abstract: Methods and systems are provided for de-noising medical images using deep neural networks. In one embodiment, a method comprises receiving a medical image acquired by an imaging system, wherein the medical image comprises colored noise; mapping the medical image to a de-noised medical image using a trained convolutional neural network (CNN); and displaying the de-noised medical image via a display device. The deep neural network may thereby reduce colored noise in the acquired noisy medical image, increasing a clarity and diagnostic quality of the image.

公开(公告)号：US20240201298A1

公开(公告)日：2024-06-20

申请号：US18067939

申请日：2022-12-19

Applicant: GE Precision Healthcare LLC

Inventor： Ali Ersoz

IPC: G01R33/48 ,  G01R33/565

CPC classification number: G01R33/4822 ,  G01R33/56509

Abstract: A method for generating an image of an object with a magnetic resonance imaging (MRI) system includes acquiring an initial set of radial k-space spokes. Based on the initial set of radial k-space spokes, a plurality of motion states of the object is estimated. A first set of radial k-space spokes are then acquired based on a pre-defined view order sequence. Based on the first set of radial k-space spokes, a motion of the object is determined. If the object motion is detected, then the pre-defined view order is adjusted. A second set of radial k-space spokes is then acquired based on the adjusted pre-defined view order. The MRI k-space is generated by distributing the radial k-space spokes having similar motion evenly across the MRI k-space. Finally, the image of the object is reconstructed based on the MRI k-space.

公开(公告)号：US12092715B2

公开(公告)日：2024-09-17

申请号：US18067939

申请日：2022-12-19

Applicant: GE Precision Healthcare LLC

Inventor： Ali Ersoz

IPC: G01R33/48 ,  G01R33/565

CPC classification number: G01R33/4822 ,  G01R33/56509

Abstract: A method for generating an image of an object with a magnetic resonance imaging (MRI) system includes acquiring an initial set of radial k-space spokes. Based on the initial set of radial k-space spokes, a plurality of motion states of the object is estimated. A first set of radial k-space spokes are then acquired based on a pre-defined view order sequence. Based on the first set of radial k-space spokes, a motion of the object is determined. If the object motion is detected, then the pre-defined view order is adjusted. A second set of radial k-space spokes is then acquired based on the adjusted pre-defined view order. The MRI k-space is generated by distributing the radial k-space spokes having similar motion evenly across the MRI k-space. Finally, the image of the object is reconstructed based on the MRI k-space.

公开(公告)号：US11474183B1

公开(公告)日：2022-10-18

申请号：US17370627

申请日：2021-07-08

Applicant: GE PRECISION HEALTHCARE LLC

Inventor： Shaorong Chang ,  Xucheng Zhu ,  Ali Ersoz ,  Ajeetkumar Gaddipati ,  Moran Wei

IPC: G01V3/00 ,  G01R33/565 ,  G01R33/561 ,  G01R33/48

Abstract: A magnetic resonance (MR) imaging method of correcting motion in precorrection MR images of a subject is provided. The method includes applying, by an MR system, a pulse sequence having a k-space trajectory of a blade being rotated in k-space. The method also includes acquiring k-space data of a three-dimensional (3D) imaging volume of the subject, the k-space data of the 3D imaging volume corresponding to the precorrection MR images and acquired by the pulse sequence. The method further includes receiving a 3D MR calibration data of a 3D calibration volume, wherein the 3D calibration volume is greater than or equal to the 3D imaging volume, jointly estimating rotation and translation in the precorrection MR images based on the k-space data of the 3D imaging volume and the calibration data, correcting motion in the precorrection images based on the estimated rotation and the estimated translation, and outputting the motion-corrected images.

公开(公告)号：US20210272240A1

公开(公告)日：2021-09-02

申请号：US16806689

申请日：2020-03-02

Applicant: GE Precision Healthcare LLC

Inventor： Daniel Litwiller ,  Xinzeng Wang ,  Ali Ersoz ,  Robert Marc Lebel ,  Ersin Bayram ,  Graeme Colin McKinnon

IPC: G06T5/00 ,  G06T7/00 ,  A61B6/00

Abstract: Methods and systems are provided for de-noising medical images using deep neural networks. In one embodiment, a method comprises receiving a medical image acquired by an imaging system, wherein the medical image comprises colored noise; mapping the medical image to a de-noised medical image using a trained convolutional neural network (CNN); and displaying the de-noised medical image via a display device. The deep neural network may thereby reduce colored noise in the acquired noisy medical image, increasing a clarity and diagnostic quality of the image.