Patents by Inventor Stefan E. Atev

Stefan E. Atev has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Synthetic visualization and quantification of perfusion-related tissue viability
    Patent number: 8532353
    Abstract: A computing system and method for generating, displaying and manipulating synthetic 2D and 3D brain tissue viability images and associated metrics from multiple perfusion maps derived from CT or other imaging system input image datasets. Stored linguistic tissue classification rules characterizing infarct, ischemic and/or normal or other tissue classes as a function of one or more perfusion parameters are used. The perfusion maps are normalized to normal brain tissue regions. Elements of the input image dataset are classified into one of the tissue classes as a function of the normalized perfusion maps and the classification rules. The classification includes ranking each of the plurality of tissue classes for elements of the input image dataset, and assigning one of the classes to elements of the dataset as a function of the ranks.
    Type: Grant
    Filed: November 23, 2011
    Date of Patent: September 10, 2013
    Assignee: Vital Images, Inc.
    Inventors: Pascal Salazar-Ferrer, Bennett W. Jackson, Stefan E. Atev
  • SYNTHETIC VISUALIZATION AND QUANTIFICATION OF PERFUSION-RELATED TISSUE VIABILITY
    Publication number: 20130131507
    Abstract: A computing system and method for generating, displaying and manipulating synthetic 2D and 3D brain tissue viability images and associated metrics from multiple perfusion maps derived from CT or other imaging system input image datasets. Stored linguistic tissue classification rules characterizing infarct, ischemic and/or normal or other tissue classes as a function of one or more perfusion parameters are used. The perfusion maps are normalized to normal brain tissue regions. Elements of the input image dataset are classified into one of the tissue classes as a function of the normalized perfusion maps and the classification rules. The classification includes ranking each of the plurality of tissue classes for elements of the input image dataset, and assigning one of the classes to elements of the dataset as a function of the ranks.
    Type: Application
    Filed: November 23, 2011
    Publication date: May 23, 2013
    Inventors: Pascal Salazar-Ferrer, Bennett W. Jackson, Stefan E. Atev