Terrence Chen - Princeton NJ, US Chao Yuan - Secaucus NJ, US Abdul Saboor Sheikh - Pittsburgh PA, US Claus Neubauer - Monmouth Junction NJ, US
Assignee:
Siemens Corporation - Iselin NJ
International Classification:
G06F 15/18
US Classification:
706 12
Abstract:
A method and framework are described for detecting changes in a multivariate data stream. A training set is formed by sampling time windows in a data stream containing data reflecting normal conditions. A histogram is created to summarize each window of data, and data within the histograms are clustered to form test distribution representatives to minimize the bulk of training data. Test data is then summarized using histograms representing time windows of data and data within the test histograms are clustered. The test histograms are compared to the training histograms using nearest neighbor techniques on the clustered data. Distances from the test histograms to the test distribution representatives are compared to a threshold to identify anomalies.
Method And System For Scale-Based Vessel Enhancement In X-Ray Angiography
Terrence Chen - Princeton NJ, US Yunqiang Chen - Plainsboro NJ, US
Assignee:
Siemens Aktiengesellschaft - Munich
International Classification:
G06K 9/00
US Classification:
382130, 382128
Abstract:
A method and system for scale-based vessel enhancement in x-ray angiography images is disclosed. An input x-ray image is denoised. A lighting field is estimated in the denoised image. Vessels are extracted from the denoised image by dividing the denoised image by the estimated lighting field. Vessels are enhanced in the input x-ray image by linearly combining the extracted vessels with the input x-ray image, resulting in an enhanced image.
Stent Viewing Using A Learning Based Classifier In Medical Imaging
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
Assignee:
Siemens Corporation - Iselin NJ
International Classification:
G06K 9/00 A61B 6/02
US Classification:
382131, 382274, 378 42
Abstract:
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.
System And Method For Coronary Digital Subtraction Angiography
Ying Zhu - Monmouth Junction NJ, US Simone Prummer - Neunkirchen am Brand, DE Terrence Chen - Princeton NJ, US Martin Ostermeier - Buckenhof, DE Dorin Comaniciu - Princeton Junction NJ, US
Assignee:
Siemens Aktiengesellschaft - Munich
International Classification:
G06K 9/00
US Classification:
382130, 382131, 382132, 378 9812
Abstract:
A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image by estimating a motion field between the mask image and the background image and performing covariance-based filtering over the estimated motion field. The mask image is then warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.
Sheng Yi - Raleigh NC, US Terrence Chen - Princeton NJ, US Peng Wang - Princeton NJ, US Dorin Comaniciu - Princeton Junction NJ, US
Assignee:
Siemens Corporation - Iselin NJ
International Classification:
G06K 9/00 A61B 6/02
US Classification:
382131, 382274, 378 42
Abstract:
A method and system for detecting and modeling a catheter in a fluoroscopic image is disclosed. Catheter tip candidates and catheter body candidates are detected in the fluoroscopic image. One of a plurality of trained shape models is fitted to the catheter tip candidates and the catheter body candidates in order to model a shape of the catheter in the fluoroscopic image.
Method And System For Guidewire Tracking In Fluoroscopic Image Sequences
Peng Wang - Princeton NJ, US Ying Zhu - Monmouth Junction NJ, US Wei Zhang - Plainsboro NJ, US Terrence Chen - Princeton NJ, US Peter Durlak - Erlangen, DE Ulrich Bill - Effeltrich, DE Dorin Comaniciu - Princeton Junction NJ, US
Assignee:
Siemens Aktiengesellschaft - Munich
International Classification:
A61B 5/05
US Classification:
600424, 600425, 382102
Abstract:
A method and system for tracking a guidewire in a fluoroscopic image sequence is disclosed. In order to track a guidewire in a fluoroscopic image sequence, guidewire segments are detected in each frame of the fluoroscopic image sequence. The guidewire in each frame of the fluoroscopic image sequence is then detected by rigidly tracking the guidewire from a previous frame of the fluoroscopic image sequence based on the detected guidewire segments in the current frame. The guidewire is then non-rigidly deformed in each frame based on the guidewire position in the previous frame.
Method And System For Guiding Catheter Detection In Fluoroscopic Images
Michael Wels - Bamberg, DE Peng Wang - Princeton NJ, US Terrence Chen - Princeton NJ, US Simone Prummer - Neunkirchen am Brand, DE Dorin Comaniciu - Princeton Junction NJ, US
A method and system for detecting a guiding catheter in a 2D fluoroscopic image is disclosed. A plurality of guiding catheter centerline segment candidates are detected in the fluoroscopic image. A guiding catheter centerline connecting an input guiding catheter centerline ending point in the fluoroscopic image with an image margin of the fluoroscopic image is detected based on the plurality of guiding catheter centerline segment candidates.
Method And System For Image Based Device Tracking For Co-Registration Of Angiography And Intravascular Ultrasound Images
Peng Wang - Princeton NJ, US Simone Prummer - Neunkirchen am Brand, DE Terrence Chen - Princeton NJ, US Dorin Comaniciu - Princeton Junction NJ, US Olivier Ecabert - Pretzfeld, DE Martin Ostermeier - Buckenhof, DE
Assignee:
Siemens Aktiengesellschaft - Munich
International Classification:
A61B 5/05 A61B 8/14 G06K 9/00
US Classification:
600427, 600462, 600467, 382128
Abstract:
A method and system for co-registration of angiography data and intra vascular ultrasound (IVUS) data is disclosed. A vessel branch is detected in an angiogram image. A sequence of IVUS images is received from an IVUS transducer while the IVUS transducer is being pulled back through the vessel branch. A fluoroscopic image sequence is received while the IVUS transducer is being pulled back through the vessel branch. The IVUS transducer and a guiding catheter tip are detected in each frame of the fluoroscopic image sequence. The IVUS transducer detected in each frame of the fluoroscopic image sequence is mapped to a respective location in the detected vessel branch of the angiogram image. Each of the IVUS images is registered to a respective location in the detected vessel branch of the angiogram image based on the mapped location of the IVUS transducer detected in a corresponding frame of the fluoroscopic image sequence.
Siemens Corporate Research - Princeton, NJ since Jul 2012
Research Group Head
Siemens Corporate Research Jun 2011 - Aug 2012
Program Manager
Siemens Corporate Research Jun 2008 - May 2011
Project Manager
Siemens Corporate Research Jun 2006 - May 2008
Research Scientist
Siemens Corporate Research Jun 2004 - Aug 2004
Summer Internship
Education:
University of Illinois at Urbana-Champaign 2000 - 2006
PhD, Computer Science
National Taiwan University 1994 - 1998
B.S., Computer Science
Skills:
Computer Vision Machine Learning Pattern Recognition Image Processing Medical Imaging Algorithms Signal Processing R&D Software Engineering Artificial Intelligence Computer Science Digital Imaging Distributed Systems Program Management Team Leadership Team Management