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Can Ceritoglu

age ~45

from Baltimore, MD

Can Ceritoglu Phones & Addresses

  • 2923 Saint Paul St, Baltimore, MD 21218 • (410)4673263

Work

  • Company:
    Johns hopkins university
    Apr 2008 to Apr 2012
  • Position:
    Postdoctoral researcher

Education

  • School / High School:
    Bilkent University

Industries

Program Development

Resumes

Can Ceritoglu Photo 1

Research Associate

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Location:
Baltimore, MD
Industry:
Program Development
Work:
Johns Hopkins University Apr 2008 - Apr 2012
Postdoctoral Researcher

Johns Hopkins Hospital Apr 2008 - Apr 2012
Research Associate
Education:
Bilkent University
The Johns Hopkins University

Us Patents

  • Advanced Cost Functions For Image Registration For Automated Image Analysis: Multi-Channel, Hypertemplate And Atlas With Built-In Variability

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  • US Patent:
    20110103672, May 5, 2011
  • Filed:
    Jul 7, 2009
  • Appl. No.:
    12/999721
  • Inventors:
    Michael I. Miller - Towson MD, US
    Susumu Mori - Ellicott City MD, US
    Anqi Qiu - Singapore, SG
    Jiangyang Zhang - Baltimore MD, US
    Can Ceritoglu - Baltimore MD, US
  • International Classification:
    G06K 9/00
    G01R 33/20
    G01N 23/00
    G01T 1/164
  • US Classification:
    382131, 324307, 378 4, 25036304
  • Abstract:
    A non-invasive imaging system, comprising: an imaging scanner; a signal processing system in communication with the imaging scanner to receive an imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit stores template data corresponding to a tissue region of a subject under observation, wherein the signal processing system is adapted to compute, using the imaging signal and the template data, refined template data corresponding to the tissue region, and wherein the refined template data incorporates subpopulation variability information associated with the tissue region such that the signal processing system provides an image of the tissue region in which a substructure is automatically identified taking into account the subpopulation variability information.

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