Patents by Inventor Kao-Chang LIN

Kao-Chang LIN 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).

  • Eye care device and method for assessing and predicting dementia
    Patent number: 11288801
    Abstract: An establishing method of a retinal layer thickness detection model includes following steps. A reference database is obtained, and an image pre-processing step, a feature selecting step, a training step and a confirming step are performed. The reference database includes reference optical coherence tomographic images. In the image pre-processing step, the reference optical coherence tomographic images are duplicated and cell segmentation lines of retinal layers are marked to obtain control optical coherence tomographic images. In the feature selecting step, the reference optical coherence tomographic images are analyzed to obtain reference image features. The training step is to train with the reference image features and obtain the retinal layer thickness detection model.
    Type: Grant
    Filed: September 28, 2020
    Date of Patent: March 29, 2022
    Assignees: NATIONAL CHIN-YI UNIVERSITY OF TECHNOLOGY, CHI MEI MEDICAL CENTER
    Inventors: Yue-Jing He, Ching-Ping Chang, Shu-Chun Kuo, Kao-Chang Lin
  • EYE CARE DEVICE AND METHOD FOR ASSESSING AND PREDICTING DEMENTIA
    Publication number: 20220036552
    Abstract: An establishing method of a retinal layer thickness detection model includes following steps. A reference database is obtained, and an image pre-processing step, a feature selecting step, a training step and a confirming step are performed. The reference database includes reference optical coherence tomographic images. In the image pre-processing step, the reference optical coherence tomographic images are duplicated and cell segmentation lines of retinal layers are marked to obtain control optical coherence tomographic images. In the feature selecting step, the reference optical coherence tomographic images are analyzed to obtain reference image features. The training step is to train with the reference image features and obtain the retinal layer thickness detection model.
    Type: Application
    Filed: September 28, 2020
    Publication date: February 3, 2022
    Inventors: Yue-Jing HE, Ching-Ping CHANG, Shu-Chun KUO, Kao-Chang LIN