Xiaoguang Lu

8218849, Jul 10, 2012

Aug 28, 2009

12/549461

Xiaoguang Lu - Plainsboro NJ, US
Bogdan Georgescu - Plainsboro NJ, US
Dorin Comaniciu - Princeton Junction NJ, US
Arne Littmann - Erlangen, DE
Edgar Mueller - Heroldsbach, DE

Siemens Corporation - Iselin NJ

A61B 6/03

382131

A method and system for detecting anatomic landmarks in medical images is disclosed. In order to detect multiple related anatomic landmarks, a plurality of landmark candidates are first detected individually using trained landmark detectors. A joint context is then generated for each combination of the landmark candidates. The best combination of landmarks in then determined based on the joint context using a trained joint context detector.

8311308, Nov 13, 2012

Dec 6, 2010

12/960625

Terrence Chen - Princeton NJ, US
Xiaoguang Lu - West Windsor NJ, US
Thomas Pohl - Marloffstein, DE
Peter Durlak - Erlangen, DE
Dorin Comaniciu - Princeton Junction NJ, US

Siemens Corporation - Iselin NJ

G06K 9/00
A61B 6/02

382131, 382274, 378 42

Stent viewing is provided in medical imaging. Stent images are provided with minimal or no user input of spatial locations. Images showing contrast agent are distinguished from other images in a sequence. After aligning non-contrast images, the images are compounded to enhance the stent. The contrast agent images are used to identify the vessel. A contrast agent image is aligned with the enhanced stent or other image to determine the relative vessel location. An indication of the vessel wall may be displayed in an image also showing the stent. A preview images may be output. A guide wire may be used to detect the center line for vessel identification. Various detections are performed using a machine-trained classifier or classifiers.

8406496, Mar 26, 2013

Jul 16, 2009

12/504047

Yefeng Zheng - Dayton NJ, US
Xiaoguang Lu - Plainsboro NJ, US
Bogdan Georgescu - Plainsboro NJ, US
Edgar Müller - Heroldsbach, DE
Dorin Comaniciu - Princeton Junction NJ, US
Arne Littmann - Erlangen, DE

Siemens Aktiengesellschaft - Munich

G06K 9/00

382131

A method and system for left ventricle (LV) detection in 2D magnetic resonance imaging (MRI) images is disclosed. In order to detect the LV in a 2D MRI image, a plurality of LV candidates are detected, for example using marginal space learning (MSL) based detection. Candidates for distinctive anatomic landmarks associated with the LV are then detected in the 2D MRI image. In particular, apex candidates and base candidates are detected in the 2D MRI image. One of the LV candidates is selected as a final LV detection result using component-based voting based on the detected LV candidates, apex candidates, and base candidates.

20090074280, Mar 19, 2009

Aug 6, 2008

12/186815

Xiaoguang Lu - Plainsboro NJ, US
Bogdan Georgescu - Plainsboro NJ, US
Yefeng Zheng - Dayton NJ, US
Joanne Otsuki - Oakland CA, US
Dorin Comaniciu - Princeton Junction NJ, US

Siemens Corporate Research, Inc. - Princeton NJ
Siemens Medical Solutions USA, Inc. - Malvern PA

A61B 5/00

382131

A plane position for a standard view is detected from three-dimensional echocardiographic data. The position of the plane within the volume is defined by translation, orientation (rotation), and/or scale. Possible positions are detected and other possible positions are ruled out. The classification of the possible positions occurs sequentially by translation, then orientation, and then scale. The sequential process may limit calculations required to identify the plane position for a desired view.

20090124886, May 14, 2009

Nov 4, 2008

12/264361

Xiaoguang Lu - Plainsboro NJ, US
Bogdan Georgescu - Plainsboro NJ, US
Daniel Fasulo - Titusville NJ, US

Siemens Corporate Research, Inc. - Princeton NJ

A61B 5/055
A61B 5/05

600410, 600407

A method for generating classifiers for identifying neuropsychiatric disease includes acquiring functional neuroimaging data. The acquired functional neuroimaging data may be registered to an atlas of the brain. A discriminative mask is generated based on the registered functional neuroimaging data and the generated discriminative mask is applied to the registered functional neuroimaging data. One or more classifiers are generated for identifying neuropsychiatric disease based on the masked functional neuroimaging data. The accuracy of the generated classifiers may be verified. The generated classifiers may then be used to identify neuropsychiatric disease.

20110144480, Jun 16, 2011

Dec 6, 2010

12/960635

Xiaoguang Lu - West Windsor NJ, US
Terrence Chen - Princeton NJ, US
Thomas Pohl - Marloffstein, DE
Peter Durlak - Erlangen, DE
Dorin Comaniciu - Princeton Junction NJ, US

Siemens Corporation - Iselin NJ
Siemens Aktiengesellschaft - Munich

A61B 5/05

600424

Stent marker detection is automatically performed. Stent markers in fluoroscopic images or other markers in other types of imaging are detected using a machine-learnt classifier. Hierarchal classification may be used, such as detecting individual markers with one classifier and then detecting groups of markers (e.g., a pair) with a joint classifier. The detection may be performed in a single image and without user indication of a location.

20120076382, Mar 29, 2012

Sep 22, 2011

13/239530

Christoph Guetter - Lawrenceville NJ, US
Jens Gühring - Erlangen, DE
Marie-Pierre Jolly - Hillsborough NJ, US
Xiaoguang Lu - West Windsor NJ, US
Hui Xue - Franklin Park NJ, US
Jeremy Collins - Chicago IL, US
Peter Weale - Worcester, GB

Siemens Corporation - Iselin NJ

G06K 9/00

382131

A method for clinical parameter derivation and adaptive flow acquisition within a sequence of magnetic resonance images includes commencing an acquisition of a sequence of images. One or more landmarks are automatically detected from within one or more images of the sequence of images. The detected one or more landmarks are propagated across subsequent images of the sequence of images. A plane is fitted to the propagation of landmarks. The positions of landmarks or alternatively the position of the fitted plane within the sequence of images is used for derivation of clinical parameters such as tissue velocities and/or performing adaptive flow acquisitions to measure blood flow properties.

20120078085, Mar 29, 2012

Sep 28, 2011

13/246910

Hui Xue - Franklin Park NJ, US
Marie-Pierre Jolly - Hillsborough NJ, US
Xiaoguang Lu - West Windsor NJ, US
Jens Gühring - Erlangen, DE

Siemens Corporation - Iselin NJ

A61B 5/055
A61B 5/02

600420

A method () of processing myocardial MR perfusion images that corrects imaging errors arising from myocardial motion and B-1 field inhomogeneity (-); segments the myocardium images (); and calculates perfusion measures that enable analysis of the segmented myocardium images ().