Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content

Table 1 Structures of the generator and discriminator, and gradient optimization conditions

From: A cycle generative adversarial network for improving the quality of four-dimensional cone-beam computed tomography images

Optimizer

Adam gradient descent method

Minibatch size

1

Initial learning rate

0.0002

Epochs

100

Encoder depth

Generator: 3, discriminator: 4

Convolution filter

Generator: 32, discriminator: 128

Residual block

6

Back to article page

Radiation Oncology

ISSN: 1748-717X

Contact us