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Is your feature request related to a problem? Please describe.
NV DLMED Researchers released publication using multi-conditional stack GAN, conclusion from their paper:
We use a multi-conditional GAN, coupled with a new structure of style control and fusion, to effectively generate realistic nodules whose appearance is controlled by its genomic features. Without erasing any portion of condition image, our method is superior over state-of-the-art method in object realism and background fusion. An end-to-end mechanism is achieved to holistically model and correlate various features. As such, our approach can provide not only an effective and controllable means to generate diverse nodules, but also a discriminative radiogemonic map linking genomic and image features. Currently, this work is proof of concept given that the data size is limited. More data and experiments will be needed to further validate this approach for radiogemonic study.
Describe the solution you'd like
Abstract creation of Generative Adversarial Networks framework and relevant components in MONAI, with one concrete example of radiogenomic GAN.
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The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
NV DLMED Researchers released publication using multi-conditional stack GAN, conclusion from their paper:
Describe the solution you'd like
Abstract creation of Generative Adversarial Networks framework and relevant components in MONAI, with one concrete example of radiogenomic GAN.
Describe alternatives you've considered
N/A
Additional context
N/A
The text was updated successfully, but these errors were encountered: