公开(公告)号：US20200249306A1

公开(公告)日：2020-08-06

申请号：US16783144

申请日：2020-02-05

Applicant: University of Virginia Patent Foundation

Inventor： Mohammad Abdishektaei ,  Xue Feng ,  Xiaoying Cai ,  Craig H. Meyer ,  Frederick H. Epstein

IPC: G01R33/565 ,  G06N20/00 ,  G01R33/48 ,  G06N3/08

Abstract: Suppressing artifacts in MRI image acquisition data includes alternatives to phase cycling by using a Convolutional Neural Network to suppress the artifact-generating echos. A U-NET CNN is trained using phase-cycled artifact-free images for ground truth comparison with received displacement encoded stimulated echo (DENSE) images. The DENSE images include data from a single acquisition with both stimulated (STE) and T1-relaxation echoes. The systems and methods of this disclosure are explained as generating artifact-free images in the ultimate output and avoiding the additional data acquisition needed for phase cycling and shortens the scan time in DENSE MRI.

公开(公告)号：US10718837B2

公开(公告)日：2020-07-21

申请号：US15493842

申请日：2017-04-21

Applicant: UNIVERSITY OF VIRGINIA PATENT FOUNDATION ,  Siemens Healthcare GmbH

Inventor： John P. Mugler, III ,  Samuel W. Fielden ,  G. Wilson Miller, IV ,  Craig H. Meyer ,  Talissa A. Altes ,  Alto Stemmer ,  Josef Pfeuffer ,  Berthold Kiefer

IPC: G01R33/48 ,  A61B5/00 ,  A61B5/055

Abstract: Some aspects of the present disclosure relate to ultrashort-echo-time (UTE) imaging. In one embodiment, a method includes acquiring UTE imaging data associated with an area of interest of a subject. The acquiring comprises applying an imaging pulse sequence with a three-dimensional (3D) spiral acquisition and a nonselective excitation pulse. The method also includes reconstructing at least one image of the area of interest from the acquired UTE imaging data.

公开(公告)号：US10557908B2

公开(公告)日：2020-02-11

申请号：US15947443

申请日：2018-04-06

Applicant: University of Virginia Patent Foundation ,  Siemens Healthcare GmbH

Inventor： Craig H. Meyer ,  John P. Mugler, III ,  Samuel W. Fielden ,  Gudrun Ruyters ,  Berthold Kiefer ,  Josef Pfeuffer

IPC: G01R33/561 ,  G01R33/563 ,  G01R33/48 ,  G01R33/565

Abstract: In some aspects, the disclosed technology relates to magnetic field monitoring of spiral echo train imaging. In one embodiment, a method for spiral echo train imaging of an area of interest of a subject includes measuring k-space values and field dynamics corresponding to each echo of a spiral echo pulse train, using a dynamic field camera and a magnetic resonance imaging (MRI) system. The dynamic field camera is configured to measure characteristics of fields generated by the MRI system; the characteristics include at least one imperfection associated with the MRI system. The spiral echo pulse train corresponds to a spiral trajectory scan from the MRI system that obtains magnetic resonance imaging data using a pulse sequence which applies spiral gradients in-plane with through-plane phase encoding. The method also includes generating, based on the characteristics of the fields measured by the dynamic field camera and based on the obtained magnetic resonance imaging data, a model of the k-space trajectory corresponding to each echo of the spiral echo pulse train; and, based on the generated model of the k-space trajectory, reconstructing images that correspond to the area of interest and that are compensated for the at least one imperfection associated with the MRI system.

公开(公告)号：US09651645B2

公开(公告)日：2017-05-16

申请号：US15078790

申请日：2016-03-23

Applicant: UNIVERSITY OF VIRGINIA PATENT FOUNDATION

Inventor： Samuel W. Fielden ,  Craig H. Meyer ,  Xue Feng

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

CPC classification number: G01R33/565 ,  G01R33/4824

Abstract: Systems, methods of reducing off-resonance blurring in acquired magnetic resonance imaging data. The method includes acquiring a first set of spiral interleaf data for each of one or more spiral-in/out interleaves by performing a first sampling each of one or more locations in k-space along a first redundant spiral-in/out trajectory, and acquiring a second set of spiral interleaf data for each of the one or more spiral-in/out interleaves by performing a second sampling of each of the one or more locations in the k-space along a second redundant spiral-in/out trajectory, wherein the second redundant spiral-in/out trajectory corresponds to a time-reversed trajectory of the first redundant spiral-in/out trajectory. The method may yet further include combining the first set of spiral interleaf data and the second set of spiral interleaf data with an averaging operation such as to reduce artifacts.

公开(公告)号：US20160202335A1

公开(公告)日：2016-07-14

申请号：US15078790

申请日：2016-03-23

Applicant: UNIVERSITY OF VIRGINIA PATENT FOUNDATION

Inventor： Samuel W. Fielden ,  Craig H. Meyer ,  Xue Feng

IPC: G01R33/48 ,  G01R33/565

CPC classification number: G01R33/565 ,  G01R33/4824

Abstract: Systems, methods of reducing off-resonance blurring in acquired magnetic resonance imaging data. The method includes acquiring a first set of spiral interleaf data for each of one or more spiral-in/out interleaves by performing a first sampling each of one or more locations in k-space along a first redundant spiral-in/out trajectory, and acquiring a second set of spiral interleaf data for each of the one or more spiral-in/out interleaves by performing a second sampling of each of the one or more locations in the k-space along a second redundant spiral-in/out trajectory, wherein the second redundant spiral-in/out trajectory corresponds to a time-reversed trajectory of the first redundant spiral-in/out trajectory. The method may yet further include combining the first set of spiral interleaf data and the second set of spiral interleaf data with an averaging operation such as to reduce artifacts.

Abstract translation: 系统，减少获取的磁共振成像数据中的非共振模糊的方法。 该方法包括：通过沿着第一冗余螺旋进/出轨迹对k空间中的一个或多个位置执行第一采样，获取一个或多个螺旋输入/输出交错中的每一个的第一组螺旋插入数据，以及 通过沿着第二冗余螺旋进/出轨迹执行所述k空间中的所述一个或多个位置中的每个位置的第二采样来获取所述一个或多个螺旋输入/输出交错中的每一个的第二组螺旋插入数据， 其中所述第二冗余螺旋进/出轨迹对应于所述第一冗余螺旋进/出轨迹的时间反转轨迹。 该方法还可以包括将第一组螺旋插入数据和第二组螺旋插值数据与平均化操作组合，以减少伪影。

公开(公告)号：US20160148378A1

公开(公告)日：2016-05-26

申请号：US14952859

申请日：2015-11-25

Applicant: UNIVERSITY OF VIRGINIA PATENT FOUNDATION

Inventor： Michael Salerno ,  Craig H. Meyer ,  Xiao Chen ,  Yang Yang ,  Frederick H. Epstein ,  Christopher M. Kramer

IPC: G06T7/00 ,  G06T15/08 ,  G06T11/00 ,  G06T7/20

CPC classification number: G06T11/003 ,  A61B5/0044 ,  A61B5/0263 ,  A61B5/055 ,  G01R33/4826 ,  G01R33/5601 ,  G01R33/5611 ,  G01R33/56366

Abstract: Some aspects of the present disclosure relate to systems and methods for three-dimensional spiral perfusion imaging. In one embodiment, a method for perfusion imaging of a subject includes acquiring perfusion imaging data associated with the heart of a subject. The acquiring includes applying an imaging pulse sequence with a three-dimensional stack-of-spirals trajectory. The method also includes reconstructing perfusion images from the acquired perfusion imaging data. The reconstructing includes parallel imaging and motion-guided compressed sensing. The method also includes determining, from the reconstructed perfusion images, absolute perfusion values based on time-intensity relationships to quantify myocardial blood flow of the heart of the subject, and generating a quantitative volumetric perfusion flow map based on the determined absolute perfusion values.

Abstract translation: 本公开的一些方面涉及用于三维螺旋灌注成像的系统和方法。 在一个实施例中，用于对象的灌注成像的方法包括获取与受试者的心脏相关联的灌注成像数据。 该采集包括应用具有三维叠加螺旋轨迹的成像脉冲序列。 该方法还包括从获取的灌注成像数据重建灌注图像。 重建包括并行成像和运动引导压缩感测。 该方法还包括根据重建的灌注图像确定基于时间 - 强度关系的绝对灌注值，以量化受试者心脏的心肌血流量，以及基于确定的绝对灌注值产生定量体积灌注流程图。

公开(公告)号：US20150285889A1

公开(公告)日：2015-10-08

申请号：US14677905

申请日：2015-04-02

Applicant: University of Virginia Patent Foundation

Inventor： Xiao Chen ,  Frederick H. Epstein ,  Yang Yang ,  Michael Salerno ,  Craig H. Meyer

IPC: G01R33/561 ,  A61B5/02 ,  A61B5/055 ,  G01R33/48 ,  G01R33/54

CPC classification number: A61B5/02 ,  A61B5/0042 ,  A61B5/0044 ,  A61B5/055 ,  G01R33/4826 ,  G01R33/546 ,  G01R33/5608 ,  G01R33/5611

Abstract: Some aspects of the present disclosure relate to accelerated imaging using variable-density sampling and compressed sensing with parallel imaging. In one embodiment, a method includes acquiring magnetic resonance data associated with a physiological activity in an area of interest of a subject. The acquiring includes performing accelerated variable-density sampling with phase-contrast displacement encoding. The method also includes reconstructing, from the acquired magnetic resonance data, images corresponding to the physiological activity in the area of interest. The reconstructing includes performing parallel imaging and compressed sensing.

Abstract translation: 本公开的一些方面涉及使用可变密度采样和具有并行成像的压缩感测的加速成像。 在一个实施例中，一种方法包括获取与受试者感兴趣区域中的生理活动相关联的磁共振数据。 该采集包括执行具有相位差位移编码的加速可变密度采样。 该方法还包括从获取的磁共振数据重建与感兴趣区域中的生理活动相对应的图像。 重建包括执行并行成像和压缩感测。

公开(公告)号：US20150282719A1

公开(公告)日：2015-10-08

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 ,  A61B5/00 ,  A61B5/055

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.

Abstract translation: 本公开的方面涉及包含先前知识的用于医学成像的系统和方法。 一些方面涉及使用非本地平均值过滤器来结合先验知识。 一些方面涉及结合用于改善灌注成像的现有知识，例如并入动脉自旋标记的那些。

公开(公告)号：US20240353514A1

公开(公告)日：2024-10-24

申请号：US18641158

申请日：2024-04-19

Applicant: University of Virginia Patent Foundation

Inventor： Craig H. Meyer ,  John P. Mugler, III ,  Grady Wilson Miller, IV ,  Sheng Chen ,  Helen L. Sporkin ,  Steven P. Allen ,  Zhixing Wang

IPC: G01R33/48 ,  G01R33/50

CPC classification number: G01R33/4814 ,  G01R33/4804 ,  G01R33/4816 ,  G01R33/50

Abstract: Described herein are systems, methods, and computer-readable medium for magnetic resonance (MR) based thermometry. 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; tracking changes in proton resonance frequency 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：US11950877B2

公开(公告)日：2024-04-09

申请号：US17428832

申请日：2020-02-05

Applicant: UNIVERSITY OF VIRGINIA PATENT FOUNDATION

Inventor： Craig H. Meyer ,  Xue Feng ,  Michael Salerno

IPC: A61B5/00 ,  A61B5/026 ,  A61B5/055 ,  G01R33/483 ,  G01R33/563 ,  G06N3/08 ,  G06T3/00 ,  G06T3/60 ,  G06T7/00 ,  G06T7/11 ,  G06T7/143 ,  G06T7/149 ,  G06T7/194 ,  G06T7/215 ,  G06T7/33 ,  G16H30/40

CPC classification number: A61B5/0044 ,  A61B5/0263 ,  A61B5/055 ,  A61B5/7267 ,  G01R33/4835 ,  G01R33/56366 ,  G06N3/08 ,  G06T3/0006 ,  G06T3/60 ,  G06T7/0014 ,  G06T7/11 ,  G06T7/143 ,  G06T7/149 ,  G06T7/194 ,  G06T7/215 ,  G06T7/33 ,  G16H30/40 ,  A61B2576/023 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30048 ,  G06T2207/30104 ,  G06T2207/30168

Abstract: A computerized system and method of modeling myocardial tissue perfusion can include acquiring a plurality of original frames of magnetic resonance imaging (MRI) data representing images of a heart of a subject and developing a manually segmented set of ground truth frames from the original frames. Applying training augmentation techniques to a training set of the originals frame of MRI data can prepare the data for training at least one convolutional neural network (CNN). The CNN can segment the training set of frames according to the ground truth frames. Applying the respective input test frames to a trained CNN can allow for segmenting an endocardium layer and an epicardium layer within the respective images of the input test frames. The segmented images can be used in calculating myocardial blood flow into the myocardium from segmented images of the input test frames.