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Dorin I Comaniciu

from Princeton, NJ
Age ~60
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Related to:
Cristina Comaniciu, 56Alexandra Comaniciu, 23
Connected to:
Adrian G Comaniciu, 57Iulia D Comanici, 41Andrea R Comanitz, 47Johanna M Comanzo, 45Scott T Comanzo, 46Barbara M Comardelle, 39Danny P Comardelle, 72Kristen M Comarell, 49Andrew M Comarsh, 58Allen Comas, 54

Dorin Comaniciu Phones & Addresses

  • 1108 Bradley Ct, Princeton, NJ 08540 (609) 497-1370
  • 2 Stuart Ln, West Windsor, NJ 08550 (609) 936-8185
  • Princeton Jct, NJ
  • Ewing, NJ
  • 126 Forest Glen Dr, Highland Park, NJ 08904 (732) 227-0388
  • Piscataway, NJ
  • Highlands, NJ

Work

Company: Siemens healthcare Apr 2018 Position: Senior vice president, artificial intelligence and digital innovation

Education

School / High School: Harvard Business School 2019 to 2019 Specialities: Education, Medicine

Skills

Development • Technology • Research • Software Development • Corporate Research • Architecture • Computer Vision

Ranks

Certificate: Executive Education, Accelerating Innovation In Precision Medicine

Industries

Hospital & Health Care

Resumes

Resumes

Dorin Comaniciu Photo 1

Senior Vice President, Artificial Intelligence And Digital Innovation

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Location:
2 Stuart Ln west, Princeton Junction, NJ 08550
Industry:
Hospital & Health Care
Work:
Siemens Healthcare
Senior Vice President, Artificial Intelligence and Digital Innovation
Siemens Healthcare Aug 2015 - Mar 2018
Vice President, Medical Imaging Technologies at Siemens Healthcare
Siemens May 2012 - Jul 2015
Head, Imaging and Computer Vision
Siemens 2008 - 2012
Global Technology Head, Image Analytics and Informatics
Siemens 2004 - 2008
Department Head, Integrated Data Systems
Education:
Harvard Business School 2019 - 2019
Stanford University Graduate School of Business 2017 - 2017
The Wharton School 2011 - 2011
Rutgers University 1996 - 2000
Doctorates, Doctor of Philosophy, Computer Engineering University Politehnica of Bucharest 1992 - 1995
Doctorates, Doctor of Philosophy, Telecommunications, Electronics University Politehnica of Bucharest 1983 - 1988
The Wharton School 1954 - 1957
Skills:
Development
Technology
Research
Software Development
Corporate Research
Architecture
Computer Vision
Certifications:
Executive Education, Accelerating Innovation In Precision Medicine
Executive Eductaion, the Innovative Healthcare Leader

Publications

Us Patents

Adaptive Resolution System And Method For Providing Efficient Low Bit Rate Transmission Of Image Data For Distributed Applications

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US Patent:
6829391, Dec 7, 2004
Filed:
Aug 31, 2001
Appl. No.:
09/944316
Inventors:
Dorin Comaniciu - Highland Park NJ
Visvanathan Ramesh - Plainsboro NJ
Fabio Berton - Finale Ligure, IT
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06K 936
US Classification:
382243, 382232
Abstract:
A client-server system and method that enables efficient, low bit rate transmission of image data over a network from an image server (e. g. , active cameras) to a client for, e. g. , distributed surveillance. A detection and tracking module detects a human presence within an observation area and provides 2-dimensional face coordinates and its estimated scale to a video transmission module. The captured video is then efficiently encoded in log-polar coordinates using an adaptive log-polar mapping, with a foveation point centered on the face. A fovea region, which covers the target object (face), is uniformly sampled and transmitted at full resolution to the client. The periphery region (background) is sampled according to a log-polar grid. To compensate for bit rate variations due to the changes in the scale of the target object and/or bandwidth of the communication channel, the resolution of the periphery region is modified through an adaptive log-polar mapping process, so as to maintain a virtually constant transmission rate from the server to the client. The high resolution of the data in the fovea region enables efficient recognition and/or identification of the transmitted video.

Vessel Detection By Mean Shift Based Ray Propagation

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US Patent:
6947040, Sep 20, 2005
Filed:
Oct 18, 2002
Appl. No.:
10/274465
Inventors:
Huseyin Tek - Princeton NJ, US
Dorin Comaniciu - Princeton NJ, US
James Williams - Princeton NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06T017/00
US Classification:
345420, 345428, 382128, 382173
Abstract:
A method for segmentation of 2D structures in CT and MR images is provided. The method is based on 2D ray propagation by mean-shift analysis with a smoothness constraint. Ray propagation is used to guide an evolving curve due to its computational efficiency and shape priors are incorporated for robust convergence. The method includes the steps of receiving 2D image data; visualizing the 2D image data on a display device; selecting a structure in the 2D image data by placing a seed in the structure; initializing a plurality of rays from the seed to form a curve; determining a speed function of each of the rays; evolving the curve by propagating the rays based on the speed function of each of the rays; converging the rays on a boundary of the structure; and segmenting the structure when all of the rays have converged on the structure's boundary.

Statistical Modeling And Performance Characterization Of A Real-Time Dual Camera Surveillance System

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US Patent:
7006950, Feb 28, 2006
Filed:
Jun 12, 2000
Appl. No.:
09/592532
Inventors:
Michael Greiffenhagen - Plainsboro NJ, US
Visvanathan Ramesh - Plainsboro NJ, US
Dorin Comaniciu - Piscataway NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06F 7/60
G06F 17/10
G06F 101/00
US Classification:
703 2, 703 6, 382107, 382228
Abstract:
The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Segmentation Of 3D Medical Structures Using Robust Ray Propagation

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US Patent:
7015907, Mar 21, 2006
Filed:
Sep 4, 2002
Appl. No.:
10/234271
Inventors:
Huseyin Tek - Princeton NJ, US
Dorin Comaniciu - Princeton NJ, US
James P. Williams - Princeton Junction NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06T 17/20
US Classification:
345423, 345419, 345426, 345427, 345581, 345583, 345589, 345621, 382128, 382173
Abstract:
A method for segmentation of 3D structures in CT and MR images is provided. The method is based on 3D ray propagation by mean-shift analysis with a smoothness constraint. Ray propagation is used to guide an evolving surface due to its computational efficiency and shape priors are incorporated for robust convergence. The method includes the steps of receiving 3D image data; visualizing the 3D image data on a display device; selecting a structure in the 3D image data by placing a seed in the structure; initializing a plurality of rays from the seed to form a surface; determining a speed function of each of the rays; evolving the surface by propagating the rays based on the speed function of each of the rays; converging the rays on a boundary of the structure; and segmenting the structure when all of the rays have converged on the structure's boundary.

Systems And Methods For Automatic Scale Selection In Real-Time Imaging

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US Patent:
7027643, Apr 11, 2006
Filed:
May 15, 2003
Appl. No.:
10/345131
Inventors:
Dorin Comaniciu - Princeton NJ, US
Visvanathan Ramesh - Plainsboro NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06K 9/00
US Classification:
382162, 382164, 382225
Abstract:
A system and method for automatic scale selection in real-time image and video processing and computer vision applications. In one aspect, a non-parametric variable bandwidth mean shift technique, which is based on adaptive estimation of a normalized density gradient, is used for detecting one or more modes in the underlying data and clustering the underlying data. In another aspect, a data-driven bandwidth (or scale) selection technique is provided for the variable bandwidth mean shift method, which estimates for each data point the covariance matrix that is the most stable across a plurality of scales. The methods can be used for detecting modes and clustering data for various types of data such as image data, video data speech data, handwriting data, etc.

Systems And Methods For Automatic Scale Selection In Real-Time Imaging

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US Patent:
7031523, Apr 18, 2006
Filed:
May 16, 2002
Appl. No.:
10/147092
Inventors:
Dorin Comaniciu - Princeton NJ, US
Visvanathan Ramesh - Plainsboro NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06K 9/46
G06K 9/66
US Classification:
382190, 382225, 382288
Abstract:
A system and method for automatic scale selection in real-time image and video processing and computer vision applications. In one aspect, a non-parametric variable bandwidth mean shift technique, which is based on adaptive estimation of a normalized density gradient, is used for detecting one or more modes in the underlying data and clustering the underlying data. In another aspect, a data-driven bandwidth (or scale) selection technique is provided for the variable bandwidth mean shift method, which estimates for each data point the covariance matrix that is the most stable across a plurality of scales. The methods can be used for detecting modes and clustering data for various types of data such as image data, video data speech data, handwriting data, etc.

Systems And Methods For Automatic Scale Selection In Real-Time Imaging

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US Patent:
7035465, Apr 25, 2006
Filed:
Jan 15, 2003
Appl. No.:
10/345094
Inventors:
Dorin Comaniciu - Princeton NJ, US
Visvanathan Ramesh - Plainsboro NJ, US
Assignee:
Siemens Corporate Research, Inc. - Princeton NJ
International Classification:
G06K 9/46
G06K 9/66
US Classification:
382190, 382255, 382288
Abstract:
A system and method for automatic scale selection in real-time image and video processing and computer vision applications. In one aspect, a non-parametric variable bandwidth mean shift technique, which is based on adaptive estimation of a normalized density gradient, is used for detecting one or more modes in the underlying data and clustering the underlying data. In another aspect, a data-driven bandwidth (or scale) selection technique is provided for the variable bandwidth mean shift method, which estimates for each data point the covariance matrix that is the most stable across a plurality of scales. The methods can be used for detecting modes and clustering data for various types of data such as image data, video data speech data, handwriting data, etc.

System And Method For Real-Time Feature Sensitivity Analysis Based On Contextual Information

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US Patent:
7087018, Aug 8, 2006
Filed:
Nov 6, 2003
Appl. No.:
10/702984
Inventors:
Dorin Comaniciu - Princeton NJ, US
Arun Krishnan - Exton PA, US
Xiang Sean Zhou - Plainsboro NJ, US
Bhavani Duggirala - Bellevue WA, US
Diane Paine - Redmond WA, US
Assignee:
Siemens Medical Solutions USA, Inc. - Malvern PA
International Classification:
A61B 5/00
A61B 8/00
US Classification:
600300, 600437
Abstract:
A system and method for assigning feature sensitivity values to a set of potential measurements to be taken during a medical procedure of a patient in order to provide a medical diagnosis is disclosed. Data is received from a sensor that represents a particular medical measurement. The received data and context data are analyzed with respect to one or more sets of training models. Feature sensitivity values are derived for the particular medical measurement and other potential measurements to be taken based the analysis, and the feature sensitivity values are outputted.

Wikipedia References

Dorin Comaniciu Photo 2

Dorin Comaniciu

Isbn (Books And Publications)

Statistical Methods In Video Processing: Eccv 2004 Workshop Smvp 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers

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Author

Dorin Comaniciu

ISBN #

3540239898

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Dorin I Comaniciu from Princeton, NJ, age ~60 Get Report