Patents by Inventor Catherine Jayapandian

Catherine Jayapandian 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).

  • Deep learning-based multi-site, multi-primitive segmentation for nephropathology using renal biopsy whole slide images
    Patent number: 11645753
    Abstract: Embodiments discussed herein facilitate segmentation of histological primitives from stained histology of renal biopsies via deep learning and/or training deep learning model(s) to perform such segmentation. One example embodiment is configured to access a first histological image of a renal biopsy comprising a first type of histological primitives, wherein the first histological image is stained with a first type of stain; provide the first histological image to a first deep learning model trained based on the first type of histological primitive and the first type of stain; and receive a first output image from the first deep learning model, wherein the first type of histological primitives is segmented in the first output image.
    Type: Grant
    Filed: September 25, 2020
    Date of Patent: May 9, 2023
    Assignees: Case Western Reserve University, The Cleveland Clinic Foundation
    Inventors: Anant Madabhushi, Catherine Jayapandian, Yijiang Chen, Andrew Janowczyk, John Sedor, Laura Barisoni
  • DEEP LEARNING-BASED MULTI-SITE, MULTI-PRIMITIVE SEGMENTATION FOR NEPHROPATHOLOGY USING RENAL BIOPSY WHOLE SLIDE IMAGES
    Publication number: 20210158524
    Abstract: Embodiments discussed herein facilitate segmentation of histological primitives from stained histology of renal biopsies via deep learning and/or training deep learning model(s) to perform such segmentation. One example embodiment is configured to access a first histological image of a renal biopsy comprising a first type of histological primitives, wherein the first histological image is stained with a first type of stain; provide the first histological image to a first deep learning model trained based on the first type of histological primitive and the first type of stain; and receive a first output image from the first deep learning model, wherein the first type of histological primitives is segmented in the first output image.
    Type: Application
    Filed: September 25, 2020
    Publication date: May 27, 2021
    Inventors: Anant Madabhushi, Catherine Jayapandian, Yijiang Chen, Andrew Janowczyk, John Sedor, Laura Barisoni