Generative adversarial network medical image generation for training of a classifier
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United States of America
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Mar 25, 2025
Grant Date -
May 28, 2020
app pub date -
Jan 30, 2020
filing date -
Jan 30, 2020
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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.
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