Invention Grant
- Patent Title: Deep learning-based multi-site, multi-primitive segmentation for nephropathology using renal biopsy whole slide images
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Application No.: US17032617Application Date: 2020-09-25
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Publication No.: US11645753B2Publication Date: 2023-05-09
- Inventor: Anant Madabhushi , Catherine Jayapandian , Yijiang Chen , Andrew Janowczyk , John Sedor , Laura Barisoni
- Applicant: Case Western Reserve University , The Cleveland Clinic Foundation
- Applicant Address: US OH Cleveland
- Assignee: Case Western Reserve University,The Cleveland Clinic Foundation
- Current Assignee: Case Western Reserve University,The Cleveland Clinic Foundation
- Current Assignee Address: US OH Cleveland; US OH Cleveland
- Agency: Eschweiler & Potashnik, LLC
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T7/00 ; G06T7/11 ; G06T11/00 ; G06T3/00 ; G06N3/04 ; G06N3/08

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.
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