Patents by Inventor Kevin Shaohua Zhou

Kevin Shaohua Zhou 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).

  • Automatic spatial context based multi-object segmentation in 3D images
    Patent number: 9218524
    Abstract: Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas.
    Type: Grant
    Filed: February 25, 2013
    Date of Patent: December 22, 2015
    Assignee: Siemens Product Lifecycle Management Software Inc.
    Inventors: Quan Wang, Dijia Wu, Meizhu Liu, Le Lu, Kevin Shaohua Zhou
  • AUTOMATIC SPATIAL CONTEXT BASED MULTI-OBJECT SEGMENTATION IN 3D IMAGES
    Publication number: 20140161334
    Abstract: Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas.
    Type: Application
    Filed: February 25, 2013
    Publication date: June 12, 2014
    Applicant: Siemens Product Lifecycle Management Software, Inc.
    Inventors: Quan Wang, Dijia Wu, Meizhu Liu, Le Lu, Kevin Shaohua Zhou