Dijia Wu

US Patent:

20110064289, Mar 17, 2011

Filed:

Sep 13, 2010

Appl. No.:

12/880385

Inventors:

Jinbo Bi - Chester Springs PA, US
Le Lu - Chalfont PA, US
Marcos Salganicoff - Bala Cynwyd PA, US
Yoshihisa Shinagawa - Downingtown PA, US
Dijia Wu - North Brunswick NJ, US

Assignee:

Siemens Medical Solutions USA, Inc. - Malvern PA

International Classification:

G06K 9/62

US Classification:

382128

Abstract:

Automated and semi-automated systems and methods for detection and classification of structures within 3D lung CT images using voxel-level segmentation and subvolume-level classification.

US Patent:

20110075920, Mar 31, 2011

Filed:

Dec 8, 2010

Appl. No.:

12/962901

Inventors:

Dijia Wu - North Brunswick NJ, US
Le Lu - Chalfont PA, US
Jinbo Bi - Chester Springs PA, US
Yoshihisa Shinagawa - Downingtown PA, US
Marcos Salganicoff - Bala Cynwyd PA, US

Assignee:

SIEMENS MEDICAL SOLUTIONS USA, INC. - Malvern PA

International Classification:

G06K 9/62

US Classification:

382160

Abstract:

Described herein is a framework for automatically classifying a structure in digital image data are described herein. In one implementation, a first set of features is extracted from digital image data, and used to learn a discriminative model. The discriminative model may be associated with at least one conditional probability of a class label given an image data observation Based on the conditional probability, at least one likelihood measure of the structure co-occurring with another structure in the same sub-volume of the digital image data is determined. A second set of features may then be extracted from the likelihood measure.

US Patent:

20120070055, Mar 22, 2012

Filed:

Sep 21, 2011

Appl. No.:

13/238370

Inventors:

David Liu - Princeton NJ, US
Dijia Wu - North Brunswick NJ, US
Shaohua Kevin Zhou - Plainsboro NJ, US
Maria Jimena Costa - Nuernberg, DE
Michael Suehling - Erlangen, DE
Christian Tietjen - Furth, DE

Assignee:

Siemens Aktiengesellschaft - Munich
Siemens Corporation - Iselin NJ

International Classification:

G06K 9/00

US Classification:

382131

Abstract:

A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.

US Patent:

20120106810, May 3, 2012

Filed:

Oct 17, 2011

Appl. No.:

13/274515

Inventors:

Sowmya Ramakrishnan - Kendall Park NJ, US
Christopher V. Alvino - Allenwood NJ, US
Dijia Wu - North Brunswick NJ, US
David Liu - Princeton NJ, US
Shaohua Kevin Zhou - Plainsboro NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G06K 9/00

US Classification:

382128

Abstract:

Ribs are automatically ordered and paired. After ordering ribs on each side, magnetic and spring functions are used to solve for rib pairing. The magnetic function is used to constrain possible pairs across sides, and the spring function is used to maintain the order on each side while accounting for missing or fused ribs.

US Patent:

20120183193, Jul 19, 2012

Filed:

Jan 3, 2012

Appl. No.:

13/342248

Inventors:

Michael Wels - Bamberg, DE
Michael Suehling - Erlangen, DE
Shaohua Kevin Zhou - Plainsboro NJ, US
David Liu - Princeton NJ, US
Dijia Wu - North Brunswick NJ, US
Christopher V. Alvino - Allenwood NJ, US
Michael Kelm - Erlangen, DE
Grzegorz Soza - Heroldsberg, DE
Dorin Comaniciu - Princeton Junction NJ, US

Assignee:

Siemens Aktiengesellschaft - Munich
Siemens Corporation - Iselin NJ

International Classification:

G06K 9/00

US Classification:

382131

Abstract:

A method and system for automatic detection and volumetric quantification of bone lesions in 3D medical images, such as 3D computed tomography (CT) volumes, is disclosed. Regions of interest corresponding to bone regions are detected in a 3D medical image. Bone lesions are detected in the regions of interest using a cascade of trained detectors. The cascade of trained detectors automatically detects lesion centers and then estimates lesion size in all three spatial axes. A hierarchical multi-scale approach is used to detect bone lesions using a cascade of detectors on multiple levels of a resolution pyramid of the 3D medical image.

US Patent:

20130070996, Mar 21, 2013

Filed:

Sep 4, 2012

Appl. No.:

13/602660

Inventors:

David Liu - Tampa FL, US
Hao Xu - Princeton NJ, US
Dijia Wu - North Brunswick NJ, US
Christian Tietjen - Furth, DE
Grzegorz Soza - Heroldsberg, DE
Shaohua Kevin Zhou - Plainsboro NJ, US
Dorin Comaniciu - Princeton Junction NJ, US

Assignee:

Siemens Aktiengesellschaft - Munich
Siemens Corporation - Iselin NJ

International Classification:

G06K 9/48
G06K 9/62
G06K 9/00

US Classification:

382131

Abstract:

A method and system for up-vector detection for ribs in a 3D medical image volume, such as a computed tomography (CT) volume is disclosed. A rib centerline of at least one rib is extracted in a 3D medical image volume. An up-vector is automatically detected at each of a plurality of centerline points of the rib centerline of the at least one rib. The up-vector at each centerline point can be detected using a trained regression function. Alternatively, the up-vector at each centerline point can be detected by detecting an ellipse shape in a cross-sectional rib image generated at each centerline point.

US Patent:

20130077841, Mar 28, 2013

Filed:

Sep 4, 2012

Appl. No.:

13/602730

Inventors:

Dijia Wu - North Brunswick NJ, US
David Liu - Tampa FL, US
Christian Tietjen - Furth, DE
Grzegorz Soza - Heroldsberg, DE
Shaohua Kevin Zhou - Plainsboro NJ, US
Dorin Comaniciu - Princeton Junction NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G06K 9/46

US Classification:

382131

Abstract:

A method and system for extracting rib centerlines in a 3D volume, such as a 3D computed tomography (CT) volume, is disclosed. Rib centerline voxels are detected in the 3D volume using a learning based detector. Rib centerlines or the whole rib cage are then extracted by matching a template of rib centerlines for the whole rib cage to the 3D volume based on the detected rib centerline voxels. Each of the extracted rib centerlines are then individually refined using an active contour model.

US Patent:

20180307895, Oct 25, 2018

Filed:

Jun 19, 2018

Appl. No.:

16/011894

Inventors:

- Redmond WA, US
Michael J. Conrad - Monroe WA, US
Dijia Wu - Sammamish WA, US
Jinyu Li - Sammamish WA, US

Assignee:

Microsoft Technology Licensing, LLC - Redmond WA

International Classification:

G06K 9/00
G06T 7/60
G06T 7/40
G06K 9/52
G06K 9/46
G06K 9/20
G06T 7/50
G06T 7/90

Abstract:

Systems and methods for identifying a false representation of a human face are provided. In one example, a method for identifying a false representation of a human face includes receiving one or more data streams captured by one or more sensors sensing a candidate face. In a plurality of stages that each comprises a different analysis, one or more of the data streams are analyzed, and the stages comprise determining whether a plurality of candidate face depth points lies on a single flat plane or a curving plane. Based at least in part on determining that the plurality of candidate face depth points lies on the single flat plane, an indication of the false representation of the human face is outputted.