Li Zhang

Author:

Li Zhang

ISBN #:

0804740305

Author:

Li Zhang

ISBN #:

0804742065

Author:

Li Zhang

ISBN #:

0824750543

Author:

Li Zhang

ISBN #:

7561432429

Author:

Li Zhang

ISBN #:

7801064542

US Patent:

7203349, Apr 10, 2007

Filed:

Jan 29, 2002

Appl. No.:

10/059848

Inventors:

Li Zhang - Plainsboro NJ, US
Li Fan - Plainsboro NJ, US
Jianzhong Qian - Princeton Junction NJ, US

Assignee:

Siemens Corporate Research, Inc. - Princeton NJ

International Classification:

G06K 9/00

US Classification:

382128, 128922, 378 4

Abstract:

A system and method for automatically reducing false-positive nodule candidates associated with airways includes receiving a nodule candidate, testing for airway cavities connected to the candidate, and recognizing the candidate as a false-positive nodule candidate if it is connected to an airway cavity; where the testing may include perpendicular testing for airways that are relatively perpendicular to an examination plane and parallel testing for airways that are relatively parallel to an examination plane.

US Patent:

7209581, Apr 24, 2007

Filed:

Jul 23, 2004

Appl. No.:

10/898511

Inventors:

Li Zhang - Skillman NJ, US
Ming Fang - Princeton Jct. NJ, US

Assignee:

Siemens Medical Solutions USA, Inc. - Malvern PA

International Classification:

G06K 9/00

US Classification:

382131, 382173

Abstract:

A system and method for ground glass nodule (GGN) segmentation is provided. The method comprises: selecting a point in a medical image, wherein the point is located in a GGN; defining a volume of interest (VOI) around the point, wherein the VOI comprises the GGN; removing a chest wall from the VOI; obtaining an initial state for a Markov random field; and segmenting the VOI, wherein the VOI is segmented using the Markov random field.

US Patent:

7289653, Oct 30, 2007

Filed:

Dec 13, 2004

Appl. No.:

11/010813

Inventors:

Li Zhang - Skillman NJ, US
Ming Fang - Princeton Jct. NJ, US

Assignee:

Siemens Corporate Research, Inc. - Princeton NJ

International Classification:

G06K 9/00

US Classification:

382131, 382173

Abstract:

A system and method for ground glass nodule (GGN) segmentation is provided. The method comprises: selecting a point in a medical image, wherein the point is located in a GGN; defining a volume of interest (VOI) around the point, wherein the VOI comprises the GGN; removing a chest wall from the VOI; obtaining an initial state for a Markov random field; segmenting the VOI, wherein the VOI is segmented using the Markov random field; identifying vessels in the volume of interest; segmenting the vessels; and removing segmented vessels from the segmented ground glass nodule.

US Patent:

7627173, Dec 1, 2009

Filed:

Jul 26, 2005

Appl. No.:

11/189288

Inventors:

Li Zhang - Skillman NJ, US
Tiantian Zhang - Troy NY, US

Assignee:

Siemens Medical Solutions USA, Inc. - Malvern PA

International Classification:

G06K 9/00
G06K 9/34

US Classification:

382173, 382128, 382132, 382154, 382131

Abstract:

A method and system for ground glass nodule (GGN) segmentation. The invention comprises methods and systems for GGN segmentation using adaptive intensity models in conjunction with Markov random field (MRF) based modeling. The adaptive intensity model overcomes problems associated with low-contrast GGN images. Vessels included by MRF segmentation are removed by shape analysis based on distance maps of the segmentation.

US Patent:

7653225, Jan 26, 2010

Filed:

Sep 16, 2004

Appl. No.:

10/942477

Inventors:

Li Zhang - Skillman NJ, US
Ming Fang - Princeton Jct. NJ, US

Assignee:

Siemens Corporation - Iselin NJ

International Classification:

G06K 9/00

US Classification:

382128, 128922

Abstract:

A method for segmentation of a ground glass nodule included in a volume of interest in a medical image and segmented by a process such as a Markov random field process, includes: identifying vessels in the volume of interest; segmenting the vessels; and removing segmented vessels from the segmented ground glass nodule.

US Patent:

7720284, May 18, 2010

Filed:

Sep 8, 2006

Appl. No.:

11/517485

Inventors:

Li Zhang - Los Angeles CA, US
Haizhou Ai - Beijing, CN
Shuichiro Tsukiji - Kyoto, JP
Shihong Lao - Kyoto, JP

Assignee:

Omron Corporation - Kyoto
Tsinghua University - Beijing

International Classification:

G06K 9/34

US Classification:

382173

Abstract:

Method and apparatus for face alignment by building a hierarchical classifier network. The hierarchical classifier network connects the tasks of face detection and face alignment into a smooth coarse-to-fine procedure. Texture classifiers are trained to recognize feature texture at different scales for different resolution layers. A multi-layer structure is employed to organize the texture classifiers, which begins with one classifier at the first layer and gradually refines the localization of feature points using additional texture classifiers in subsequent layers.

US Patent:

7747051, Jun 29, 2010

Filed:

Oct 2, 2006

Appl. No.:

11/537675

Inventors:

Li Zhang - Skillman NJ, US

Assignee:

Siemens Medical Solutions USA, Inc. - Malvern PA

International Classification:

G06K 9/00
G06K 9/46

US Classification:

382128, 382190, 128922

Abstract:

A method and system for differentiating a vessel and a nodule within an image. The method and system first identifies a complex object in the image and then identifies portions of the complex object as a vessel or a nodule using a distance transform based method. A simplex object is identified in the image and the simplex object is identified as a vessel or a nodule using compactness values. Complex objects are analyzed using features in a distance transform map to identify a) nodule parts and b) vessels that are attached to or pass through the nodule parts.

US Patent:

7747052, Jun 29, 2010

Filed:

Nov 2, 2006

Appl. No.:

11/555817

Inventors:

Jing Huo - Los Angeles CA, US
Li Zhang - Skillman NJ, US
Carol L. Novak - Newtown PA, US

Assignee:

Siemens Medical Solutions USA, Inc. - Malvern PA

International Classification:

G06K 9/00
A61B 6/00

US Classification:

382128, 378 21

Abstract:

A method for detecting solid components in ground glass nodules (GGNs) in medical images, includes: performing an intensity-based segmentation on a segmented GGN to identify a high intensity region; and performing a shape analysis to determine whether the high intensity region is a solid component or a vessel, wherein the shape analysis comprises: computing a compactness of the high intensity region; and determining whether the high intensity region is a solid component or a vessel by using an area, a maximum distance on a distance transform map and the compactness of the region; or determining whether the high intensity region is a solid component or a vessel by scaling and normalizing the region and computing a compactness for the scaled and normalized region.