- Patent Title: Hough transform-based vascular network disorder features on baseline fluorescein angiography scans predict response to anti-VEGF therapy in diabetic macular edema
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Application No.: US16415184Application Date: 2019-05-17
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Publication No.: US10970838B2Publication Date: 2021-04-06
- Inventor: Anant Madabhushi , Prateek Prasanna , Justis Ehlers , Sunil Srivastava
- Applicant: Case Western Reserve University , The Cleveland Clinic Foundation
- Applicant Address: US OH Cleveland; 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: G06T7/00
- IPC: G06T7/00 ; G06T5/50 ; G16H30/20 ; G16H30/40 ; G16H50/30 ; G06K9/00 ; G16B50/30

Abstract:
Embodiments facilitate prediction of anti-vascular endothelial growth (anti-VEGF) therapy response in DME or RVO patients. A first set of embodiments discussed herein relates to training of a machine learning classifier to determine a prediction for response to anti-VEGF therapy based on a vascular network organization via Hough transform (VaNgOGH) descriptor generated based on FA images of tissue demonstrating DME or RVO. A second set of embodiments discussed herein relates to determination of a prediction of response to anti-VEGF therapy for a DME or RVO patient (e.g., non-rebounder vs. rebounder, response vs. non-response) based on a VaNgOGH descriptor generated based on FA imagery of the patient.
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