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A Generative Adversarial Network (GAN) can be trained, where the GAN includes an anomaly-removing Generator network configured to modify a medical image to remove a depiction of a biological anomaly and one or more Discriminator networks (each configured to discriminate between real and fake images)...

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Bibliographische Detailangaben
Hauptverfasser: CARANO, Richard Alan Duray, PETROV, Yury Anatolievich
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:A Generative Adversarial Network (GAN) can be trained, where the GAN includes an anomaly-removing Generator network configured to modify a medical image to remove a depiction of a biological anomaly and one or more Discriminator networks (each configured to discriminate between real and fake images). The anomaly-removing Generator network can then receive a medical image that depicts a particular biological anomaly (or pre-processed version thereof) and generate a modified image predicted to lack any depiction of the particular biological anomaly. The size of the particular biological anomaly may be estimated based on the modified image and the received image (or pre-processed version thereof).