Invention Grant
- Patent Title: Medical image classification based on a generative adversarial network trained discriminator
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Application No.: US15850116Application Date: 2017-12-21
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Publication No.: US10937540B2Publication Date: 2021-03-02
- Inventor: Ali Madani , Mehdi Moradi , Tanveer F. Syeda-Mahmood
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent Stephen J. Walder, Jr.; William J. Stock
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06K9/62 ; G06N3/04 ; G16H30/40 ; G16H50/50 ; G06T7/00

Abstract:
Mechanisms are provided to implement a generative adversarial network (GAN). A discriminator of the GAN is configured to discriminate input medical images into a plurality of classes including a first class indicating a medical image representing a normal medical condition, a second class indicating an abnormal medical condition, and a third class indicating a generated medical image. A generator of the GAN generates medical images and a training medical image set is input to the discriminator that includes labeled medical images, unlabeled medical images, and generated medical images. The discriminator is trained to classify training medical images in the training medical image set into corresponding ones of the first, second, and third classes. The trained discriminator is applied to a new medical image to classify the new medical image into a corresponding one of the first class or second class. The new medical image is either labeled or unlabeled.
Public/Granted literature
- US20190198156A1 Medical Image Classification Based on a Generative Adversarial Network Trained Discriminator Public/Granted day:2019-06-27
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