Invention Grant
- Patent Title: Histomorphometric classifier to predict cardiac failure from whole-slide hematoxylin and eosin stained images
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Application No.: US15799129Application Date: 2017-10-31
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Publication No.: US10528848B2Publication Date: 2020-01-07
- Inventor: Anant Madabhushi , Jeffrey John Nirschl , Andrew Janowczyk , Eliot G. Peyster , Michael D. Feldman , Kenneth B. Margulies
- Applicant: Case Western Reserve University
- Applicant Address: US OH Cleveland
- Assignee: Case Western Reserve University
- Current Assignee: Case Western Reserve University
- Current Assignee Address: US OH Cleveland
- Agency: Eschweiler & Potashnik, LLC
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06N3/08 ; G06N3/04 ; G06T3/40 ; G06K9/20 ; G16H50/20

Abstract:
Methods, apparatus, and other embodiments predict heart failure from WSIs of cardiac histopathology using a deep learning convolutional neural network (CNN). One example apparatus includes a pre-processing circuit configured to generate a pre-processed WSI by downsampling a digital WSI; an image acquisition circuit configured to randomly select a set of non-overlapping ROIs from the pre-processed WSI, and configured to provide the set of non-overlapping ROIs to a deep learning circuit; a deep learning circuit configured to generate an image-level probability that a member of the set of non-overlapping ROIs is a failure/abnormal pathology ROI using a CNN; and a classification circuit configured to generate a patient-level probability that the patient from which the region of tissue represented in the WSI was acquired is experiencing failure or non-failure based, at least in part, on the image-level probability.
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