Patents by Inventor Abdullah Hussein OWAIDH

Abdullah Hussein OWAIDH 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).

  • Method, system and computer program product for breast density classification using parts-based local features
    Patent number: 9519966
    Abstract: An automated content-based image retrieval method, a system and a computer program product for the classification of breast density from mammographic imagery. Raw digital mammogram images taken of patients are initially pre-processed to remove noise and enhance contrast, then subjected to pectoral muscle segmentation to produce region of interest (ROI) images. The ROI images are then decomposed using non-negative matrix factorization (NMF), where a non-negative sparsity constraint and reconstruction quality measures are imposed on the extracted and retained first few NMF factors. Based on the retained NMF factors, kernel matrix-based support vector machines classify the mammogram images binomially or multinomially to breast density categories.
    Type: Grant
    Filed: July 13, 2015
    Date of Patent: December 13, 2016
    Assignee: King Fahd University of Petroleum and Minerals
    Inventors: Lahouari Ghouti, Abdullah Hussein Owaidh
  • METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR BREAST DENSITY CLASSIFICATION USING PARTS-BASED LOCAL FEATURES
    Publication number: 20160314579
    Abstract: An automated content-based image retrieval method, a system and a computer program product for the classification of breast density from mammographic imagery. Raw digital mammogram images taken of patients are initially pre-processed to remove noise and enhance contrast, then subjected to pectoral muscle segmentation to produce region of interest (ROI) images. The ROI images are then decomposed using non-negative matrix factorization (NMF), where a non-negative sparsity constraint and reconstruction quality measures are imposed on the extracted and retained first few NMF factors. Based on the retained NMF factors, kernel matrix-based support vector machines classify the mammogram images binomially or multinomially to breast density categories.
    Type: Application
    Filed: July 13, 2015
    Publication date: October 27, 2016
    Applicant: King Fahd University of Petroleum and Minerals
    Inventors: Lahouari GHOUTI, Abdullah Hussein OWAIDH