Jun Liu

US Patent:

20160247089, Aug 25, 2016

Filed:

Aug 24, 2015

Appl. No.:

14/834365

Inventors:

- Cary NC, US
Jun Liu - Cary NC, US
James Allen Cox - Cary NC, US

Assignee:

SAS Institute, Inc. - Cary NC

International Classification:

G06N 99/00

Abstract:

A system for machine training can comprise one or more data processors and a non-transitory computer-readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform operations including: accessing a dataset comprising data tracking a plurality of features; determining a series of values for a regularization parameter of a sparse support vector machine model, the series including an initial regularization value and a next regularization value; computing an initial solution to the sparse support vector machine model for the initial regularization value; identifying, using the initial solution, inactive features of the sparse support vector machine model for the next regularization value; and computing a next solution to the sparse support vector machine model for the next regularization value, wherein computing the next solution includes excluding the inactive features.

US Patent:

20140133724, May 15, 2014

Filed:

Oct 15, 2013

Appl. No.:

14/054003

Inventors:

Jun Liu - Cary NC, US
Zhili Yang - West Windsor NJ, US
Mariappan S. Nadar - Plainsboro NJ, US
Nirmal Janardhanan - Plainsboro NJ, US
Michael Zenge - Nuernberg, DE
Edgar Mueller - Heroldsbach, DE
Qiu Wang - Princeton NJ, US
Axel Loewe - Karlsruhe, DE

Assignee:

Siemens Aktiengesellschaft - Munich
Siemens Corporation - Iselin NJ

International Classification:

G06T 11/00

US Classification:

382131

Abstract:

A computer-implemented method for reconstruction of a magnetic resonance image includes acquiring a first incomplete k-space data set comprising a plurality of first k-space lines spaced according to an acceleration factor and one or more calibration lines. A parallel imaging reconstruction technique is applied to the first incomplete k-space data to determine a plurality of second k-space lines not included in the first incomplete k-space data set, thereby yielding a second incomplete k-space data set. Then, the parallel imaging reconstruction technique is applied to the second incomplete k-space data to determine a plurality of third k-space lines not included in the second incomplete k-space data, thereby yielding a complete k-space data set.

US Patent:

20140126796, May 8, 2014

Filed:

Oct 29, 2013

Appl. No.:

14/065498

Inventors:

Nicolas Chesneau - Pont-Saint-Martin, FR
Nirmal Janardhanan - Plainsboro NJ, US
Jun Liu - Cary NC, US
Mariappan S. Nadar - Plainsboro NJ, US
Qiu Wang - Princeton NJ, US
Zhili Yang - West Windsor NJ, US

Assignee:

SIEMENS CORPORATION - Iselin NJ

International Classification:

G06T 11/00
G06T 7/20

US Classification:

382131

Abstract:

A method of image reconstruction for a magnetic resonance imaging (MRI) system includes obtaining k-space scan data captured by the MRI system, the k-space scan data being representative of an undersampled region over time, iteratively reconstructing preliminary dynamic images for the undersampled region from the k-space scan data via optimization of a first instance of a minimization problem, the minimization problem including a regularization term weighted by a weighting parameter array, generating a motion determination indicative of an extent to which each location of the undersampled region exhibits motion over time based on the preliminary dynamic images, and iteratively reconstructing motion-compensated dynamic images for the region from the k-space scan data via optimization of a second instance of the minimization problem, the second instance having the weighting parameter array altered as a function of the motion determination.

US Patent:

20140085318, Mar 27, 2014

Filed:

Sep 19, 2013

Appl. No.:

14/031374

Inventors:

Mariappan S. Nadar - Plainsboro NJ, US
Steven Martin - Columbus OH, US
Alban Lefebvre - Jersey City NJ, US
Jun Liu - Cary NC, US

Assignee:

SIEMENS CORPORATION - Iselin NJ

International Classification:

G06T 7/00

US Classification:

345502

Abstract:

A system for performing image reconstruction in a multi-threaded computing environment includes one or more central processing units executing a plurality of k-space components and a plurality of graphic processing units executing a reconstruction component. The k-space components executing on the central processing units include a k-space sample data component operating in a first thread and configured to receive k-space sample data from a first file interface; a k-space sample coordinate data component operating in a second thread and configured to receive k-space sample coordinate data from a second file interface; and a k-space sample weight data component operating in a third thread and configured to retrieve k-space sample weight data from a third file interface. The reconstruction component is configured to receive one or more k-space input data buffers comprising the k-space sample data, the k-space sample coordinate data, and the k-space sample weight data from the one or more central processing units, and reconstruct an image based on the input data buffers using an iterative reconstruction algorithm.

US Patent:

20140086469, Mar 27, 2014

Filed:

Sep 25, 2013

Appl. No.:

14/036352

Inventors:

Alban Lefebvre - Jersey City NJ, US
Jun Liu - Cary NC, US
Edgar Mueller - Heroldsbach, DE
Mariappan S. Nadar - Plainsboro NJ, US
Michaela Schmidt - Uttenreuth, DE
Michael Zenge - Nuernberg, DE
Qiu Wang - Princeton NJ, US

Assignee:

SIEMENS AKTIENGESELLSCHAFT - Munich
SIEMENS CORPORATION - Iselin NJ

International Classification:

G06T 11/00

US Classification:

382131

Abstract:

A method of image reconstruction for a magnetic resonance imaging (MRI) system having a plurality of coils includes obtaining k-space scan data captured by the MRI system, the k-space scan data being representative of an undersampled region over time, determining a respective coil sensitivity profile for the region for each coil of the plurality of coils, and iteratively reconstructing dynamic images for the region from the k-space scan data via an optimization of a minimization problem. The minimization problem is based on the determined coil sensitivity profiles and redundant Haar wavelet transforms of the dynamic images.

US Patent:

20140088899, Mar 27, 2014

Filed:

Sep 27, 2013

Appl. No.:

14/038958

Inventors:

Jun Liu - Cary NC, US
Hui Xue - Franklin Park NJ, US
Marcel Dominik Nickel - Erlangen, DE
Mariappan S. Nadar - Plainsboro NJ, US
Alban Lefebvre - Jersey City NJ, US
Edgar Mueller - Heroldsbach, DE
Qiu Wang - Princeton NJ, US
Zhili Yang - West Windsor NJ, US
Nirmal Janardhanan - Plainsboro NJ, US
Michael Zenge - Nürnberg, DE

Assignee:

SIEMENS AKTIENGESELLSCHAFT - Munich
SIEMENS CORPORATION - Iselin NJ

International Classification:

G01R 33/24

US Classification:

702 65

Abstract:

A method for estimating a coil sensitivity map for a magnetic resonance (MR) image includes providing a matrix A of sliding blocks of a 3D image of coil calibration data, calculating a left singular matrix V from a singular value decomposition of A corresponding to τ leading singular values, calculating P=VV, calculating a matrix S that is an inverse Fourier transform of a zero-padded matrix P, and solving Mc=(S)cfor c, where cis a vector of coil sensitivity maps for all coils at spatial location r, and