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Options | Description |
|---|---|
RCAN | For denoising and super-resolution. This is also the model used by our Nature Methods papaer. https://www.nature.com/articles/s41592-021-01155-x |
UNet | For virtual staining and segmentation |
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Number of Filters
Default: 32
Description: Number of features (i.e. number of output channels of each convolution layer). Increase the number if for model complexity, reduce for speed up the training.
Number of Residual Blocks
Default: 3
Description: Number of residual blocks in each residual group
Number of Residual Groups
Default: 3
Description: Number of residual groups
Channel Reduction Factor
Default: 8
Description: Channel reduction factor for the squeeze-and-excitation module.
UNet Specific Parameters
Depth
Number of Initial Filter
Filter Growth Factor
Normalization Type
Channel Reduction Factor
Use Attention Gate
Activation Type at the Last Layer
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2. Training Parameters
This tab define how are we going to update the model weights during training
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