Christopher R Kramer

US Patent:

8440167, May 14, 2013

Filed:

Oct 26, 2009

Appl. No.:

13/126029

Inventors:

George A. Beller - Charlottesville VA, US
David K. Glover - Charlottesville VA, US
Alexander L. Klibanov - Charlottesville VA, US
Craig H. Meyer - Charlottesville VA, US
Dayuan Li - Charlottesville VA, US
Amit Patel - Chicago IL, US
Christopher M. Kramer - Charlottesville VA, US

Assignee:

University of Virginia Patent Foundation - Charlottesville VA

International Classification:

A61K 49/16
A61K 51/10
A61K 51/12
A61K 39/395
A61B 5/055
C07K 16/00

US Classification:

424 137, 424 149, 424 153, 424 9321, 4241431

Abstract:

The present invention provides multiple modalities for detecting LOX-1. More particularly, an imaging composition is provided that allows for the in vivo imaging of atherosclerotic plaque.

US Patent:

20100191099, Jul 29, 2010

Filed:

Jan 29, 2010

Appl. No.:

12/696433

Inventors:

Michael Salerno - Charlottesville VA, US
Frederick H. Epstein - Charlottesville VA, US
Christopher M. Kramer - Charlottesville VA, US

Assignee:

UNIVERSITY OF VIRGINIA PATENT FOUNDATION - Charlottesville VA

International Classification:

A61B 5/055

US Classification:

600420

Abstract:

A system and method for providing a dark-blood technique for contrast-enhanced cardiac magnetic resonance, improving visualization of subendocardial infarcts or perfusion abnormalities that may otherwise be difficult to distinguish from the bright blood pool. In one technique the dark-blood preparation is performed using a driven-equilibrium fourier transform (DEFT) preparation with motion sensitizing gradients which attenuate the signal in the ventricular cavities related to incoherent phase losses resulting from non-steady flow within the heart. This dark-blood preparation preserves the underlying contrast characteristics of the pulse sequence causing a myocardial infarction to be bright while rendering the blood pool dark. When applied to perfusion imaging, this dark-blood preparation will help eliminate artifacts resulting from the juxtaposition of a bright ventricular cavity and relatively dark myocardium.

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:

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:

20190279361, Sep 12, 2019

Filed:

Mar 7, 2019

Appl. No.:

16/295939

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

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:

20160148378, May 26, 2016

Filed:

Nov 25, 2015

Appl. No.:

14/952859

Inventors:

- Charlottesville VA, US
Craig H. Meyer - Charlottesville VA, US
Xiao Chen - Charlottesville VA, US
Yang Yang - Charlottesville VA, US
Frederick H. Epstein - Charlottesville VA, US
Christopher M. Kramer - Charlottesville VA, US

International Classification:

G06T 7/00
G06T 15/08
G06T 11/00
G06T 7/20

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.