公开(公告)号：US11921179B2

公开(公告)日：2024-03-05

申请号：US17732181

申请日：2022-04-28

Applicant: University of Virginia Patent Foundation

Inventor： Zhixing Wang ,  Steven P. Allen ,  Xue Feng ,  John P. Mugler, III ,  Craig H. Meyer

IPC: G01R33/48 ,  G01R33/54 ,  G01R33/56 ,  G01R33/561 ,  G01R33/565

CPC classification number: G01R33/482 ,  G01R33/543 ,  G01R33/5608 ,  G01R33/5617 ,  G01R33/56509

Abstract: Methods, computing devices, and magnetic resonance imaging systems that improve image quality in turbo spiral echo (TSE) imaging are disclosed. With this technology, a TSE pulse sequence is generated that includes a series of radio frequency (RF) refocusing pulses to produce a corresponding series of nuclear magnetic resonance (NMR) spin echo signals. A gradient waveform including a plurality of segments is generated. The plurality of segments collectively comprise a spiral ring retraced in-out trajectory. During an interval adjacent to each of the series of RF refocusing pulses, a first gradient pulse is generated according to the gradient waveform. The first gradient pulses encode the NMR spin echo signals. An image is then constructed from digitized samples of the NMR spin echo signals obtained based at least in part on the encoding.

公开(公告)号：US11647915B2

公开(公告)日：2023-05-16

申请号：US14677891

申请日：2015-04-02

Applicant: University of Virginia Patent Foundation

Inventor： Samuel Fielden ,  Li Zhao ,  Max Wintermark ,  Craig H. Meyer

IPC: A61B5/026 ,  A61B5/055 ,  A61B5/00 ,  A61B6/00

CPC classification number: A61B5/0263 ,  A61B5/0042 ,  A61B5/055 ,  A61B6/5229 ,  A61B2576/026

Abstract: Aspects of the present disclosure relate to systems and methods for medical imaging that incorporate prior knowledge. Some aspects relate to incorporating prior knowledge using a non-local means filter. Some aspects relate to incorporating prior knowledge for improved perfusion imaging, such as those incorporating arterial spin labeling.

公开(公告)号：US11644520B2

公开(公告)日：2023-05-09

申请号：US17144319

申请日：2021-01-08

Applicant: University of Virginia Patent Foundation

Inventor： Yekaterina K. Gilbo ,  Helen L. Sporkin ,  Samuel W. Fielden ,  John P. Mugler, III ,  Grady W. Miller, IV ,  Steven P. Allen ,  Craig H. Meyer

IPC: G01R33/48 ,  G01R33/561 ,  G01R33/38 ,  G01R33/50

CPC classification number: G01R33/4814 ,  G01R33/3804 ,  G01R33/4816 ,  G01R33/4818 ,  G01R33/50 ,  G01R33/561

Abstract: Described herein are systems, methods, and computer-readable medium for magnetic resonance (MR) based thermometry. In one aspect, in accordance with one embodiment, a method for magnetic resonance based thermometry includes: acquiring, by a variable flip-angle T1 mapping sequence, MR data in an area of interest of a subject that is heated by the application of focused ultrasound (FUS) to the brain of the subject, where the MR data includes T1 values over time, and where the acquisition of the MR data includes applying an accelerated three-dimensional ultra-short spiral acquisition sequence with a nonselective excitation pulse; and determining, based at least in part on a mathematical relationship established by T1 mapping thermometry, a temperature change in the area of interest over time, and where the temperature change is caused at least in part by a change in the applied FUS.

公开(公告)号：US20220373630A1

公开(公告)日：2022-11-24

申请号：US17733967

申请日：2022-04-29

Applicant: University of Virginia Patent Foundation

Inventor： Quan Dou ,  Zhixing Wang ,  Xue Feng ,  John P. Mugler, III ,  Craig H. Meyer

IPC: G01R33/56 ,  G01R33/561

Abstract: Training a neural network to correct motion-induced artifacts in magnetic resonance images includes acquiring motion-free magnetic resonance image (MRI) data of a target object and applying a spatial transformation matrix to the motion-free MRI data. Multiple frames of MRI data are produced having respective motion states. A Non-uniform Fast Fourier Transform (NUFFT) can be applied to generate respective k-space data sets corresponding to each of the multiple frames of MRI; the respective k-space data sets can be combined to produce a motion-corrupted k-space data set and an adjoint NUFFT can be applied to the motion-corrupted k-space data set. Updated frames of motion-corrupted MRI data can be formed. Using the updated frames of motion corrupted MRI data, a neural network can be trained that generates output frames of motion free MRI data; and the neural network can be saved.

公开(公告)号：US20210287367A1

公开(公告)日：2021-09-16

申请号：US17335518

申请日：2021-06-01

Applicant: University of Virginia Patent Foundation

Inventor： Craig H. Meyer ,  Anudeep Konda ,  Christopher M. Kramer ,  Xue Feng

IPC: G06T7/00 ,  G06T7/62 ,  G06T7/13 ,  G06T7/70 ,  G06K9/62 ,  A61B5/029 ,  A61B5/026 ,  A61B5/00 ,  A61B5/107 ,  G06T7/11

Abstract: In one aspect the disclosed technology relates to embodiments of a method which, includes acquiring magnetic resonance imaging data, for a plurality of images, of the heart of a subject. The method also includes segmenting, using cascaded convolutional neural networks (CNN), respective portions of the images corresponding to respective epicardium layers and endocardium layers for a left ventricle (LV) and a right ventricle (RV) of the heart. The segmenting is used for extracting biomarker data from segmented portions of the images and, in one embodiment, assessing hypertrophic cardiomyopathy from the biomarker data. The method further includes segmenting processes for T1 MRI data and LGE MRI data.

公开(公告)号：US20210208225A1

公开(公告)日：2021-07-08

申请号：US17144319

申请日：2021-01-08

Applicant: University of Virginia Patent Foundation

Inventor： Yekaterina K. Gilbo ,  Helen L. Sporkin ,  Samuel W. Fielden ,  John P. Mugler, III ,  Grady W. Miller, IV ,  Steven P. Allen ,  Craig H. Meyer

IPC: G01R33/48 ,  G01R33/50 ,  G01R33/38 ,  G01R33/561

Abstract: Described herein are systems, methods, and computer-readable medium for magnetic resonance (MR) based thermometry. In one aspect, in accordance with one embodiment, a method for magnetic resonance based thermometry includes: acquiring, by a variable flip-angle T1 mapping sequence, MR data in an area of interest of a subject that is heated by the application of focused ultrasound (FUS) to the brain of the subject, where the MR data includes T1 values over time, and where the acquisition of the MR data includes applying an accelerated three-dimensional ultra-short spiral acquisition sequence with a nonselective excitation pulse; and determining, based at least in part on a mathematical relationship established by T1 mapping thermometry, a temperature change in the area of interest over time, and where the temperature change is caused at least in part by a change in the applied FUS.

公开(公告)号：US11024025B2

公开(公告)日：2021-06-01

申请号：US16295939

申请日：2019-03-07

Applicant: University of Virginia Patent Foundation

Inventor： Craig H. Meyer ,  Anudeep Konda ,  Christopher M. Kramer ,  Xue Feng

IPC: G06T7/00 ,  G06T7/62 ,  G06T7/13 ,  G06T7/70 ,  G06K9/62 ,  A61B5/029 ,  A61B5/026 ,  A61B5/00 ,  A61B5/107 ,  G06T7/11

Abstract: In one aspect the disclosed technology relates to embodiments of a method which, includes acquiring magnetic resonance imaging data, for a plurality of images, of the heart of a subject. The method also includes segmenting, using cascaded convolutional neural networks (CNN), respective portions of the images corresponding to respective epicardium layers and endocardium layers for a left ventricle (LV) and a right ventricle (RV) of the heart. The segmenting is used for extracting biomarker data from segmented portions of the images and, in one embodiment, assessing hypertrophic cardiomyopathy from the biomarker data. The method further includes segmenting processes for T1 MRI data and LGE MRI data.

公开(公告)号：US20150287222A1

公开(公告)日：2015-10-08

申请号：US14677866

申请日：2015-04-02

Applicant: University of Virginia Patent Foundation

Inventor： Li Zhao ,  Craig H. Meyer

IPC: G06T11/00

CPC classification number: G01R33/50 ,  G01R33/5619

Abstract: Some aspects of the present disclosure relate to tissue parameter mapping. In one embodiment of the present disclosure, a method includes receiving undersampled k-space data corresponding to a dynamic physiological process in an area of interest of a subject. The method also includes estimating, from the undersampled k-space data, one or more respective tissue parameter values representing a respective state of the dynamic process at each point in time of a predetermined plurality of points in time during the acquisition. The estimation includes unscented Kalman filtering. The method also includes generating one or more tissue parameter maps using the respective plurality of estimated tissue parameter values.

Abstract translation: 本公开的一些方面涉及组织参数映射。 在本公开的一个实施例中，一种方法包括在对象的感兴趣区域中接收与动态生理过程相对应的欠采样k空间数据。 该方法还包括从欠采样的k空间数据中估计一个或多个相应的组织参数值，其表示在采集期间的预定多个时间点的每个时间点的动态过程的相应状态。 估计包括无密码卡尔曼滤波。 该方法还包括使用相应的多个估计的组织参数值来生成一个或多个组织参数图。

公开(公告)号：US20240394844A1

公开(公告)日：2024-11-28

申请号：US18642776

申请日：2024-04-22

Applicant: University of Virginia Patent Foundation

Inventor： Quan Dou ,  Xue Feng ,  Craig H. Meyer

IPC: G06T5/60 ,  G06T5/70 ,  G06T11/00

Abstract: A computer implemented method of training a deep learning convolutional neural network (CNN) to correct output magnetic resonance images includes acquiring magnetic resonance image (MRI) data for a region of interest of a subject and saving the MRI data in frames of k-space data. The method includes calculating ground truth image data from the frames k-space data. The method includes corrupting the k-space data with real noise additions into the lines of the k-space data and saving in computer memory, training pairs a ground truth frame and a corrupted frame with real noise additions. By applying the training pairs to a U-Net convolutional neural network, the method trains the U-Net to adjust output images by correcting the output images for the real noise additions.

公开(公告)号：US20240272258A1

公开(公告)日：2024-08-15

申请号：US18402593

申请日：2024-01-02

Applicant: University of Virginia Patent Foundation

Inventor： Zhixing Wang ,  Rajiv Ramasawmy ,  Ahsan Javed ,  John P. Mugler, III ,  Craig H. Meyer ,  Adrienne E. Campbell

IPC: G01R33/561 ,  G01R33/58

CPC classification number: G01R33/5615 ,  G01R33/586

Abstract: Acquiring 3D MRI data using spiral-in-out encoding trajectories includes calculating a variable flip angle RF series for use as refocusing pulses, wherein the RF series includes a plurality of refocusing RF pulses. A spoiler gradient waveform is applied along the spoiler gradient direction, wherein the computer alternately adds and subtracts partition encoding waveforms to the spoiler gradient waveform. The method reads MRI data from each encoding step during an MRI sequence. The MRI sequence inserts a spiral-in gradient before a first refocusing RF pulse from the RF sequence, overlaps a pre-winder lobe for the encoding trajectory with the spoiler gradient waveform having the partition encoding waveforms added therein, and overlaps a rewinder lobe for the encoding trajectory with the spoiler gradient waveform having the partition encoding waveforms subtracted there from.