Patents by Inventor Yoav DUEK

Yoav DUEK 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).

  • Systems and methods for generating clinically relevant images that preserve physical attributes of humans while protecting personal identity
    Patent number: 12154274
    Abstract: There is provided a method of generating a dataset of synthetic images, comprising: for each real image each depicting a real human anatomical structure: extracting and preserving a real anatomical structure region(s) from the real image, generating a synthetic image comprising a synthetic human anatomical structure region and the preserved real anatomical structure region(s), designating pairs of images, each including the real image and the synthetic image, feeding the pair into a machine learning model trained to recognize anatomical structure parts to obtain an outcome of a similarity value denoting an amount of similarity between the real image and the synthetic image, verifying that the synthetic image does not depict the real human anatomical structure when the similarity value is below a threshold, wherein an identity of the real human anatomical structure is non-determinable from the synthetic image, and including the verified synthetic image in the dataset.
    Type: Grant
    Filed: December 28, 2023
    Date of Patent: November 26, 2024
    Assignee: RealizeMD Ltd.
    Inventors: Stanislav Khirman, Uri Neeman, Alon Gat, David P. Rapaport, Yoav Duek
  • SYSTEMS AND METHODS FOR GENERATING CLINICALLY RELEVANT IMAGES THAT PRESERVE PHYSICAL ATTRIBUTES OF HUMANS WHILE PROTECTING PERSONAL IDENTITY
    Publication number: 20240135534
    Abstract: There is provided a method of generating a dataset of synthetic images, comprising: for each real image each depicting a real human anatomical structure: extracting and preserving a real anatomical structure region(s) from the real image, generating a synthetic image comprising a synthetic human anatomical structure region and the preserved real anatomical structure region(s), designating pairs of images, each including the real image and the synthetic image, feeding the pair into a machine learning model trained to recognize anatomical structure parts to obtain an outcome of a similarity value denoting an amount of similarity between the real image and the synthetic image, verifying that the synthetic image does not depict the real human anatomical structure when the similarity value is below a threshold, wherein an identity of the real human anatomical structure is non-determinable from the synthetic image, and including the verified synthetic image in the dataset.
    Type: Application
    Filed: December 28, 2023
    Publication date: April 25, 2024
    Applicant: RealizeMD Ltd.
    Inventors: Stanislav KHIRMAN, Uri NEEMAN, Alon GAT, David P. RAPAPORT, Yoav DUEK