Greg George Zaharchuk

US Patent:

20060267584, Nov 30, 2006

Filed:

May 24, 2005

Appl. No.:

11/136194

Inventors:

Reed Busse - San Mateo CA, US
John Pauly - Redwood City CA, US
Greg Zaharchuk - San Francisco CA, US

International Classification:

G01V 3/00

US Classification:

324309000

Abstract:

Methods and systems for generating T-weighted images are provided. The method includes acquiring a pair of single-shot fast-spin-echo (SSFSE) images Sand S. The method further includes generating a T-weighted image Sbased on Sand S.

US Patent:

20110245656, Oct 6, 2011

Filed:

Mar 31, 2010

Appl. No.:

12/798280

Inventors:

Roland Bammer - Palo Alto CA, US
Greg Zaharchuk - Stanford CA, US

International Classification:

A61B 5/055

US Classification:

600411, 600419

Abstract:

Arterial spin labeling MRI is used to provide a patient specific correction factor to correct a image provided by a non-ASL imaging modality (e.g., DSC MRI). More specifically, a first blood flow image is taken using the non-ASL imaging modality, and a corresponding second blood flow image is taken with ASL. Some or all of the voxels in the first image are selected according to a predetermined selection method. A correction factor (CF) is computed to be the ratio of second image BF to first image BF averaged over the selected voxels. Thus, CF is the average of ASL/non-ASL blood flow over the selected voxels. This correction factor is applied to all voxels of an image equally, but can differ from patient to patient. This correction can be applied to one or more non-ASL blood flow images.

US Patent:

20220223231, Jul 14, 2022

Filed:

Jan 13, 2022

Appl. No.:

17/647950

Inventors:

- Stanford CA, US
Greg Zaharchuk - Stanford CA, US

Assignee:

The Board of Trustees of the Leland Stanford Junior University - Stanford CA

International Classification:

G16B 40/20
G16B 5/20
G06N 20/00
G06N 3/02

Abstract:

Methods and systems for predicting biomarker progression in medical imaging is provided. A predictive model can be utilized to predict progression of a medical disorder as determined by progression of the predicted biomarker. Further, the predicted biomarker progression can be utilized to identify individuals that are fast progressors, moderate progressors, slow progressors. In some instances, the enrollment within clinical trials or treatment regimens are determined based on biomarker progression.

US Patent:

20210027436, Jan 28, 2021

Filed:

Feb 14, 2019

Appl. No.:

16/966125

Inventors:

- Schenetady NY, US
- Stanford CA, US
Greg ZAHARCHUK - Palo Alto CA, US
John M. PAULY - Palo Alto CA, US

International Classification:

G06T 5/00
G06T 5/50
A61B 5/055
G06T 7/00

Abstract:

Methods and systems for synthesizing contrast images from a quantitative acquisition are disclosed. An exemplary method includes performing a quantification scan, using a trained deep neural network to synthesize a contrast image from the quantification scan, and outputting the contrast image synthesized by the trained deep neural network. In another exemplary method, an operator can identify a target contrast type for the synthesized contrast image. A trained discriminator and classifier module determines whether the synthesized contrast image is of realistic image quality and whether the synthesized contrast image matches the target contrast type.

US Patent:

20200381096, Dec 3, 2020

Filed:

Jun 3, 2020

Appl. No.:

16/892158

Inventors:

- Stanford CA, US
Greg Zaharchuk - Stanford CA, US

Assignee:

The Board of Trustees of the Leland Stanford Junior University - Stanford CA

International Classification:

G16H 20/10
G16H 20/40
G16H 50/30
G16H 30/20
G16H 10/60
G06K 9/62
G06N 20/00
G06N 3/08

Abstract:

Methods of performing experimental treatments on a cohort of subjects are provided. A predictive model can be utilized to predict progression of a medical disorder or relevant imaging biomarker. The predicted medical disorder progression can be utilized as a control to determine whether an experimental treatment has an effect on the progression of the medical disorder. In some instances, the enrollment of subjects within a control group for clinical experiment is eliminated or reduced.

US Patent:

20190369191, Dec 5, 2019

Filed:

May 31, 2019

Appl. No.:

16/427599

Inventors:

- Stanford CA, US
Greg Zaharchuk - Stanford CA, US
John M. Pauly - Stanford CA, US
Morteza Mardani Korani - Palo Alto CA, US

International Classification:

G01R 33/56
G06T 7/00
G01R 33/48
G16H 30/40
A61B 5/055
G01R 33/483

Abstract:

A method for diagnostic imaging includes measuring undersampled data y with a diagnostic imaging apparatus; linearly transforming the undersampled data y to obtain an initial image estimate {tilde over (x)}; applying the initial image estimate {tilde over (x)} as input to a generator network to obtain an aliasing artifact-reduced image x as output of the generator network, where the aliasing artifact-reduced image x is a projection onto a manifold of realistic images of the initial image estimate {tilde over (x)}; and performing an acquisition signal model projection of the aliasing artifact-reduced x onto a space of consistent images to obtain a reconstructed image {circumflex over (x)} having suppressed image artifacts.

US Patent:

20190250233, Aug 15, 2019

Filed:

Feb 9, 2018

Appl. No.:

15/892960

Inventors:

- SCHENECTADY NY, US
- PALO ALTO CA, US
GREG ZAHARCHUK - STANFORD CA, US
JOHN PAULY - STANFORD CA, US

Assignee:

GENERAL ELECTRIC COMPANY - SCHENECTADY NY
THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY - PALO ALTO CA

International Classification:

G01R 33/561
G01R 33/54

Abstract:

A system for magnetic resonance imaging an object via a stochastic optimization of a sampling function is provided. The system includes a magnet assembly and a controller. The magnet assembly is operative to acquire MR data from the object. The controller is operative to: acquire a first MR data set using the magnet assembly; select the sampling function from a plurality of sampling function candidates based at least in part on the stochastic optimization; and acquire a second MR data set from the object using the magnet assembly based at least in part on the sampling function.

US Patent:

20180286037, Oct 4, 2018

Filed:

Mar 31, 2017

Appl. No.:

15/475760

Inventors:

Greg Zaharchuk - Stanford CA, US
Enhao Gong - Stanford CA, US
John M. Pauly - Stanford CA, US

International Classification:

G06T 7/00
G06T 3/60

Abstract:

A method of improving diagnostic and functional imaging is provided by obtaining at least two input images of a subject, using a medical imager, where each input image includes a different contrast, generating a plurality of copies of the input images using non-local mean (NLM) filtering, using an appropriately programmed computer, where each input image copy of the subject includes different spatial characteristics, obtaining at least one reference image of the subject, using the medical imager, where the reference image includes imaging characteristics that are different form the input images of the subject, training a deep network model, using data augmentation on the appropriately programmed computer, to adaptively tune model parameters to approximate the reference image from an initial set of the input and reference images, with the goal of outputting an improved quality image of other sets of low SNR low resolution images, for analysis by a physician.