Xue Feng

US Patent:

20130307536, Nov 21, 2013

Filed:

Apr 22, 2013

Appl. No.:

13/867922

Inventors:

Xue Feng - Charlottesville VA, US
Michael Salerno - Charlottesville VA, US
Christopher M. Kramer - Charlottesville VA, US
Craig H. Meyer - Charlottesville VA, US

Assignee:

UNIVERSITY OF VIRGINIA LICENSING & VENTURES GROUP - Charlottesville VA

International Classification:

G01R 33/48

US Classification:

324309, 324322

Abstract:

Systems and methods for Cartesian dynamic imaging are disclosed. In one aspect, in accordance with one example embodiment, a method includes acquiring magnetic resonance data for an area of interest of a subject that is associated with one or more physiological activities of the subject and performing image reconstruction comprising Kalman filtering or smoothing on Cartesian images associated with the acquired magnetic resonance data. Performing the image reconstruction includes increasing at least one of spatial and temporal resolution of the Cartesian images.

US Patent:

20220373627, Nov 24, 2022

Filed:

Apr 28, 2022

Appl. No.:

17/732181

Inventors:

- Charlottesville VA, US
Steven P. Allen - Charlottesville VA, US
Xue Feng - Zion Crossroads VA, US
Craig H. Meyer - Charlottesville VA, US

Assignee:

University of Virginia Patent Foundation - Charlottesville VA

International Classification:

G01R 33/48
G01R 33/561
G01R 33/56
G01R 33/54
G01R 33/565

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.

US Patent:

20220373630, Nov 24, 2022

Filed:

Apr 29, 2022

Appl. No.:

17/733967

Inventors:

- Charlottesville VA, US
Zhixing Wang - Charlottesville VA, US
Xue Feng - Zion Crossroads VA, US
Craig H. Meyer - Charlottesville VA, US

International Classification:

G01R 33/56
G01R 33/561

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.

US Patent:

20220349970, Nov 3, 2022

Filed:

Apr 29, 2022

Appl. No.:

17/733970

Inventors:

- Charlottesville VA, US
Xue Feng - Zion Crossroads VA, US
Michael Salerno - Charlottesville VA, US
Adrienne E. Campbell-Washburn - Charlottesville VA, US
Craig H. Meyer - Charlottesville VA, US

International Classification:

G01R 33/48
G01R 33/561
G01R 33/54
G01R 33/565
G01R 33/44

Abstract:

Systems and methods for performing ungated magnetic resonance imaging are disclosed herein. A method includes producing magnetic resonance image MRI data by scanning a target in a low magnetic field with a pulse sequence having a spiral trajectory; sampling k-space data from respective scans in the low magnetic field and receiving at least one field map data acquisition and a series of MRI data acquisitions from the respective scans; forming a field map and multiple sensitivity maps in image space from the field map data acquisition; forming target k-space data with the series of MRI data acquisitions; forming initial magnetic resonance images in the image domain by applying a Non-Uniform Fast Fourier Transform to the target k-space data; and forming reconstructed images with a low rank plus sparse (L+S) reconstruction algorithm applied to the initial magnetic resonance images.

US Patent:

20220188602, Jun 16, 2022

Filed:

Apr 24, 2020

Appl. No.:

17/605078

Inventors:

- Charlottesville VA, US
Xue FENG - Charlottesville VA, US

International Classification:

G06N 3/04
G06N 3/08
A61B 5/055
G06T 5/00
G01R 33/56

Abstract:

Systems and methods for denoising a magnetic resonance (MR) image utilize an unsupervised deep convolutional neural network (U-DCNN). Magnetic resonance (MR) image data of an area of interest of a subject can be acquired, which can include noisy input images that comprise noise data and noise free image data. For each of the noisy input images, iterations can be run of a converging sequence in an unsupervised deep convolutional neural network. In each iteration, parameter settings are updated; the parameter settings are used in calculating a series of image feature sets with the U-DCNN. The image feature sets predict an output image. The converging sequence of the U-DCNN is terminated before the feature sets predict a respective output image that replicates all of the noise data from the noisy input image. Based on a selected feature set, a denoised MR image of the area of interest of the subject can be output.

US Patent:

20210287367, Sep 16, 2021

Filed:

Jun 1, 2021

Appl. No.:

17/335518

Inventors:

- Charlottesville VA, US
Anudeep Konda - Los Angeles CA, US
Christopher M. Kramer - Charlottesville VA, US
Xue Feng - Charlottesville VA, US

International Classification:

G06T 7/00
G06T 7/62
G06T 7/13
G06T 7/70
G06K 9/62
A61B 5/029
A61B 5/026
A61B 5/00
A61B 5/107
G06T 7/11

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.

US Patent:

20210267455, Sep 2, 2021

Filed:

Feb 3, 2021

Appl. No.:

17/166604

Inventors:

- Charlottesville VA, US
Changyu Sun - Charlottesville VA, US
Xue Feng - Zion Crossroads VA, US
Craig H. Meyer - Charlottesville VA, US
Frederick H. Epstein - Charlottesville VA, US

International Classification:

A61B 5/00
G01R 33/56
A61B 5/02
G06T 7/00
G06T 7/11
G16H 30/40
G06N 3/08

Abstract:

A method of cardiac strain analysis uses displacement encoded magnetic resonance image (MRI) data of a heart of the subject and includes generating a phase image for each frame of the displacement encoded MRI data. Phase images include potentially phase-wrapped measured phase values corresponding to pixels of the frame. A convolutional neural network CNN computes a wrapping label map for the phase image, and the wrapping label map includes a respective number of phase wrap cycles present at each pixel in the phase image. Computing an unwrapped phase image includes adding a respective phase correction to each of the potentially-wrapped measured phase values of the phase image, and the phase correction is based on the number of phase wrap cycles present at each pixel. Computing myocardial strain follows by using the unwrapped phase image for strain analysis of the subject.

US Patent:

20210272274, Sep 2, 2021

Filed:

Oct 25, 2019

Appl. No.:

15/734521

Inventors:

- Beijing, CN
Wenzhi WANG - Beijing, CN
Xue FENG - Charlottesville VA, US
Ling SONG - Beijing, CN
Lan QIN - Beijing, CN

International Classification:

G06T 7/00
G16H 30/20
G06T 7/11

Abstract:

A method and a system for measuring morphological parameters of an intracranial aneurysm image, the method comprises: segmenting an intracranial parent artery image from three-dimensional DICOM data of DSA (S); segmenting the intracranial aneurysm image on the intracranial aneurysm image (S); and measuring morphological parameters of the intracranial aneurysm image (S). The method and the system for measuring the morphological parameters of the intracranial aneurysm image as disclosed may implement automated measurement of the intracranial aneurysm image, quickly measure morphological parameters of the intracranial aneurysm image, and guarantee consistency between measurements of morphological parameters of the aneurysm image.