Patents by Inventor Sehyo Yune

Sehyo Yune 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).

  • System and method for analyzing medical images to detect and classify a medical condition using machine-learning and a case pertinent radiology atlas
    Patent number: 11972567
    Abstract: A system for analyzing medical images to detect and classify a medical condition, the system includes an input for receiving a medical image, a convolutional neural network coupled to the input and configured to analyze the medical image to generate a prediction including a probability of the presence of the medical condition in the medical image and an atlas creation module coupled to the convolutional neural network and configured to generate an atlas comprising a set of image features and a set of training images. Each image feature is assigned with at least one training image associated with the medical condition. The system further includes a prediction basis selection module coupled to the convolutional neural network and the atlas and configured to create a prediction basis for the prediction generated by the convolutional neural network.
    Type: Grant
    Filed: May 29, 2019
    Date of Patent: April 30, 2024
    Assignee: The General Hospital Corporation
    Inventors: Hyunkwang Lee, Sehyo Yune, Synho Do
  • SYSTEM AND METHOD FOR ANALYZING MEDICAL IMAGES TO DETECT AND CLASSIFY A MEDICAL CONDITION USING MACHINE-LEARNING AND A CASE PERTINENT RADIOLOGY ATLAS
    Publication number: 20210217167
    Abstract: A system for analyzing medical images to detect and classify a medical condition, the system includes an input for receiving a medical image, a convolutional neural network coupled to the input and configured to analyze the medical image to generate a prediction including a probability of the presence of the medical condition in the medical image and an atlas creation module coupled to the convolutional neural network and configured to generate an atlas comprising a set of image features and a set of training images. Each image feature is assigned with at least one training image associated with the medical condition. The system further includes a prediction basis selection module coupled to the convolutional neural network and the atlas and configured to create a prediction basis for the prediction generated by the convolutional neural network.
    Type: Application
    Filed: May 29, 2019
    Publication date: July 15, 2021
    Inventors: Hyunkwang Lee, Sehyo Yune, Synho Do