Invention Grant
- Patent Title: Generative adversarial network medical image generation for training of a classifier
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Application No.: US17528566Application Date: 2021-11-17
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Publication No.: US11645833B2Publication Date: 2023-05-09
- Inventor: Ali Madani , Mehdi Moradi , Tanveer F. Syeda-Mahmood
- Applicant: MERATIVE US L.P.
- Applicant Address: US MI Ann Arbor
- Assignee: MERATIVE US L.P.
- Current Assignee: MERATIVE US L.P.
- Current Assignee Address: US MI Ann Arbor
- Agent Stephen J. Walder, Jr.
- Main IPC: G16H30/40
- IPC: G16H30/40 ; G16H30/20 ; G06T7/00 ; A61B6/00 ; G06N5/02 ; G06N20/00 ; G06N3/08 ; G06N3/04 ; G06K9/62 ; G06N5/022 ; G06N3/082

Abstract:
Mechanisms are provided to implement a machine learning training model. The machine learning training model trains an image generator of a generative adversarial network (GAN) to generate medical images approximating actual medical images. The machine learning training model augments a set of training medical images to include one or more generated medical images generated by the image generator of the GAN. The machine learning training model trains a machine learning model based on the augmented set of training medical images to identify anomalies in medical images. The trained machine learning model is applied to new medical image inputs to classify the medical images as having an anomaly or not.
Public/Granted literature
- US20220076075A1 Generative Adversarial Network Medical Image Generation for Training of a Classifier Public/Granted day:2022-03-10
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