Patents by Inventor Jeffrey Keith Smith

Jeffrey Keith Smith 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).

  • Methods, systems, and computer readable media for smart image protocoling
    Patent number: 11139068
    Abstract: A method for smart image protocoling includes, using a medical imaging device, obtaining, using a first medical imaging sequence, a first set of medical images of a patient. Anatomical and, if present, disease features are extracted from the first set of medical images. A machine learning trained algorithm is used to determine, in real time, and based on the extracted anatomical and/or disease features, whether a desired medical imaging goal is achieved for the patient. In response to determining that the desired medical imaging goal is achieved, at least one image from the first set of medical images is output as a final image. In response to determining that the desired medical imaging goal has not been achieved, the machine learning trained algorithm is used to select a second medical imaging sequence. A second set of medical images of the patient is obtained using the second medical imaging sequence. The above outlined procedures will be repeated until the final imaging goal is achieved for a patient.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: October 5, 2021
    Assignee: THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
    Inventors: Weili Lin, Dinggang Shen, Jeffrey Keith Smith
  • METHODS, SYSTEMS, AND COMPUTER READABLE MEDIA FOR SMART IMAGE PROTOCOLING
    Publication number: 20190228857
    Abstract: A method for smart image protocoling includes, using a medical imaging device, obtaining, using a first medical imaging sequence, a first set of medical images of a patient. Anatomical and, if present, disease features are extracted from the first set of medical images. A machine learning trained algorithm is used to determine, in real time, and based on the extracted anatomical and/or disease features, whether a desired medical imaging goal is achieved for the patient. In response to determining that the desired medical imaging goal is achieved, at least one image from the first set of medical images is output as a final image. In response to determining that the desired medical imaging goal has not been achieved, the machine learning trained algorithm is used to select a second medical imaging sequence. A second set of medical images of the patient is obtained using the second medical imaging sequence. The above outlined procedures will be repeated until the final imaging goal is achieved for a patient.
    Type: Application
    Filed: November 6, 2017
    Publication date: July 25, 2019
    Inventors: Weili Lin, Dinggang Shen, Jeffrey Keith Smith