Alban Lefebvre

US Patent:

20130121554, May 16, 2013

Filed:

Sep 14, 2012

Appl. No.:

13/616484

Inventors:

Jun Liu - Plainsboro NJ, US
Jeremy Rapin - Paris, FR
Alban Lefebvre - Plainsboro NJ, US
Mariappan S. Nadar - Plainsboro NJ, US
Michael Zenge - Nurnberg, DE
Edgar Müller - Heroldsbach, DE

International Classification:

G06T 11/00

US Classification:

382131

Abstract:

A method for image reconstruction includes receiving under-sampled k-space data, determining a data fidelity term of a first image of the under-sampled k-space data in view of a second image of the under-sampled k-space data, wherein a time component separated the first image and the second image, determining a spatial penalization on redundant Haar wavelet coefficients of the first image in view of the second image, and optimizing the first image according the data fidelity term and the spatial penalization, wherein the spatial penalization selectively penalizes temporal coefficients and an optimized image of the first image is output.

US Patent:

20130259343, Oct 3, 2013

Filed:

Feb 27, 2013

Appl. No.:

13/778446

Inventors:

Jun Liu - Plainsboro, US
Alban Lefebvre - Jersey City NJ, US
Mariappan Nadar - Plainsboro NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G06T 11/00

US Classification:

382131

Abstract:

A method for reconstructing parallel magnetic resonance images includes providing a set of acquired k-space MR image data y, and finding a target MR image x that minimizes ∥Fv−y∥+λ∥z∥where v=Sx and z=Wx where S is a diagonal matrix containing sensitivity maps of coil elements in an MR receiver array, F is an FFT matrix, W is a redundant Haar wavelet matrix, and λ≧0 is a regularization parameter, by updatingwhere k is an iteration counter, μand μare parameters of an augmented Lagrangian function, and band bare dual variables of the augmented Lagrangian.

US Patent:

20130289912, Oct 31, 2013

Filed:

Feb 28, 2013

Appl. No.:

13/779999

Inventors:

Jun Liu - Plainsboro NJ, 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 - Ithaca NY, US
Zhili Yang - West Windsor NJ, US
Nirmal Janardhanan - Plainsboro NJ, US
Michael Zenge - Nurnberg, DE

Assignee:

Siemens Aktiengesellschaft - Munchen
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 2D 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

US Patent:

20130320974, Dec 5, 2013

Filed:

Dec 18, 2012

Appl. No.:

13/717842

Inventors:

Jun Liu - Plainsboro NJ, US
Jeremy Rapin - Paris, FR
Alban Lefebvre - Jersey City NJ, US
Mariappan S. Nadar - Plainsboro NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G01R 33/48

US Classification:

324309

Abstract:

A method for parallel magnetic resonance imaging (MRI) reconstruction of digital images includes providing a set of acquired k-space MR image data v, a redundant Haar wavelet matrix W satisfying WW=I, wherein I is an identity matrix, a regularization parameter λ≧0, and a counter limit k, initializing a variable z=Wv, and intermediate quantities p=q=0, calculating y=arg min1/2∥z−(p+z)∥+λ∥z∥for 0≦i≦k, wherein z denotes values of an MR image sought to be reconstructed, updating p=(p+z)−y, updating z=arg min1/2∥z−(q+z)∥+g(z), whereinand updating q=(q+y)−z, wherein x=Wz is a solution ofthat specifies a reconstruction of the MR image.

US Patent:

20140037228, Feb 6, 2014

Filed:

Jul 25, 2013

Appl. No.:

13/950535

Inventors:

Alban Lefebvre - Jersey City NJ, US
Axel Loewe - Monmouth Junction NJ, US
Mariappan S. Nadar - Plainsboro NJ, US
Jun Liu - Plainsboro NJ, US

Assignee:

SIEMENS CORPORATION - Iselin NJ

International Classification:

G06T 1/20

US Classification:

382304

Abstract:

A computer-implemented method for calculating a multi-dimensional wavelet transform in an image processing system comprising a plurality of computation units includes receiving multi-dimensional image data. An overlap value corresponding to a number of non-zero filter coefficients associated with the multi-dimensional wavelet transform is identified. Then the multi-dimensional image data is divided into a plurality of multi-dimensional arrays, wherein the multi-dimensional arrays overlap in each dimension by a number of pixels equal to the overlap value. A multi-dimensional wavelet transform is calculated for each multi-dimensional array, in parallel, across the plurality of computation units.

US Patent:

20130113816, May 9, 2013

Filed:

Jul 2, 2012

Appl. No.:

13/539863

Inventors:

Sandra Sudarsky - Bedminster NJ, US
Mariappan S. Nadar - Plainsboro NJ, US
Shanhui Sun - Iowa city IA, US
Alban Lefebvre - Jersey City NJ, US
Bernhard Geiger - Cranbury NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G09G 5/02
G06T 11/20

US Classification:

345589, 345440

Abstract:

A method for visualizing brain connectivity includes receiving image data including molecular diffusion of brain tissue, constructing a tree data structure from the image data, wherein the tree data structure comprises a plurality of network nodes, wherein each network node is connected to a root of the tree data structure, rendering a ring of a radial layout depicting the tree data structure, wherein a plurality of vertices may be traversed from the top to the bottom, duplicating at least one control point for spline edges sharing a common ancestor, and bundling spline edges by applying a global strength parameter β.

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.